Heart Rate Variability and Hypothermia

**47**

**Chapter 4**

**Abstract**

**1. Introduction**

sufficiently addresses these issues.

ρ ∙ *c* ∙ (

flow rate of heat other than by diffusion.

where ρ is density (g/m3

the dynamics of heat balance in solids, simplified as:

Modeling Thermoregulatory

*Adam W. Potter, David P. Looney, Xiaojiang Xu,* 

*William R. Santee and Shankar Srinivasan*

Responses to Cold Environments

The ability to model and simulate the rise and fall of core body temperature is of significant interest to a broad spectrum of organizations. These organizations include the military, as well as both public and private health and medical groups. To effectively use cold models, it is useful to understand the first principles of heat transfer within a given environment as well as have an understanding of the underlying physiology, including the thermoregulatory responses to various conditions and activities. The combination of both rational or first principles and empirical approaches to modeling allow for the development of practical models that can predict and simulate core body temperature changes for a given individual and ultimately provide protection from injury or death. The ability to predict these maximal potentials within complex and extreme environments is difficult. The present work outlines biomedical modeling techniques to simulate and predict cold-

related injuries, and discusses current and legacy models and methods.

**Keywords:** hypothermia, cold injury, clothing, military, biophysics, survival

Mitigating hot and cold injuries is a complex problem and has been shown to have significant links to a number of individualized factors, to include race, gender, job specialty, and geographic origin [1, 2]. There are many other individualized elements (e.g., fitness, body composition, and genetics) that are intuitively linked to these health outcomes; however, there is a lack of adequate data to scale that

The history of characterizing heat exchange and thermoregulatory functions in humans can be traced back to the late 1770s; where British military physiologist, Sir Charles Blagden conducted descriptive studies of man, dog, and beef steak responses in a hot room [3]. Mathematically describing heat exchange theory has roots in physics and with the development of the laws of thermodynamics and heat exchange, specifically as described in Fourier's law [4] a mathematical expression of

<sup>∂</sup>*<sup>t</sup>* ) <sup>=</sup> <sup>∇</sup>*<sup>k</sup>* <sup>∇</sup>*<sup>T</sup>* <sup>+</sup> *<sup>H</sup>* (1)

), c is specific heat [(kcal/°K. kg)], *k* is heat conduc-

\_\_\_ ∂*T*

tance [kcal/(hr cm °K)], *T* is temperature (°K), t is time (hours), and *H* is the net

#### **Chapter 4**

## Modeling Thermoregulatory Responses to Cold Environments

*Adam W. Potter, David P. Looney, Xiaojiang Xu, William R. Santee and Shankar Srinivasan*

#### **Abstract**

The ability to model and simulate the rise and fall of core body temperature is of significant interest to a broad spectrum of organizations. These organizations include the military, as well as both public and private health and medical groups. To effectively use cold models, it is useful to understand the first principles of heat transfer within a given environment as well as have an understanding of the underlying physiology, including the thermoregulatory responses to various conditions and activities. The combination of both rational or first principles and empirical approaches to modeling allow for the development of practical models that can predict and simulate core body temperature changes for a given individual and ultimately provide protection from injury or death. The ability to predict these maximal potentials within complex and extreme environments is difficult. The present work outlines biomedical modeling techniques to simulate and predict coldrelated injuries, and discusses current and legacy models and methods.

**Keywords:** hypothermia, cold injury, clothing, military, biophysics, survival

#### **1. Introduction**

Mitigating hot and cold injuries is a complex problem and has been shown to have significant links to a number of individualized factors, to include race, gender, job specialty, and geographic origin [1, 2]. There are many other individualized elements (e.g., fitness, body composition, and genetics) that are intuitively linked to these health outcomes; however, there is a lack of adequate data to scale that sufficiently addresses these issues.

The history of characterizing heat exchange and thermoregulatory functions in humans can be traced back to the late 1770s; where British military physiologist, Sir Charles Blagden conducted descriptive studies of man, dog, and beef steak responses in a hot room [3]. Mathematically describing heat exchange theory has roots in physics and with the development of the laws of thermodynamics and heat exchange, specifically as described in Fourier's law [4] a mathematical expression of the dynamics of heat balance in solids, simplified as:

$$
\rho \cdot \mathcal{L} \cdot \left(\frac{\partial T}{\partial t}\right) = \nabla k \cdot \nabla T + H \tag{1}
$$

where ρ is density (g/m3 ), c is specific heat [(kcal/°K. kg)], *k* is heat conductance [kcal/(hr cm °K)], *T* is temperature (°K), t is time (hours), and *H* is the net flow rate of heat other than by diffusion.

Key work by Pennes in 1948 [5], reported measured temperatures of tissue and blood at the forearm and enabled the creation of the bioheat transfer equation. This equation has proven to be a key underlying basis of future models, seen as:

$$\nabla \cdot \mathbf{k} \cdot \nabla T + q\_p + q\_m - \mathcal{W}\_{\mathbb{G}} \{T - T\_d\} \quad = \ \rho c\_p \Big(\frac{\partial T}{\partial t}\Big) \tag{2}$$

where *k* (w/m °C) is the tissue thermal conductivity, *T* is tissue temperature in °C, *qp* (w/m3 ) is energy deposition rate, *qm* (w/m3 ) is metabolism, *W* (kg/m3 /s) is local tissue blood perfusion rate, *Cb* (J/kg/°C) is specific blood heat, *Ta* (°C) is arterial temperature, *ρ* (kg/m3 ) is the tissue density, and *cp* (J/kg/°C) is the specific tissue heat.

Conceptually, heat exchange between the human and the environment was first described by Lefevre in 1911; where he characterized the human as a sphere with an internal core that exchanged heat through the shell into the environment [6]. In 1934, Burton applied Fourier's law, presenting this exchange mathematically and describing the human as one uniform cylinder in what is considered by many as the first visual conceptualization of human thermoregulatory modeling [7].

Representation of the human in a thermoregulatory model is most often done by sectioning the human into nodes, segments, and elements; typically using one of four different designs, (1) one-node, (2) two-node, (3) multi-node, or (4) multi-element [8]. An example of the difference between these designs is shown in **Figure 1**; while the multi-element approach is more realistic human shape (e.g., finite analysis distribution). Typically each node represents an independent layer with unique thermal properties, each segment represents a section or grouped section of an area of the body, and each element represents multiple thermal components that make up the whole body (often more geometrically accurate to the shape of the human).

One node models are essentially empirically derived and do not include elements within the thermoregulatory response system. There are several one node thermoregulatory models that have been used extensively over time to predict core body temperature and thermal discomfort within a given environment [9–12].

Simple two-node models describe specific thermodynamic responses of a single segment, typically separated into concentric core and shell nodes. They have often been used examine thermal discomfort and physiological responses, to include the work by Gagge and Nishi [13–15], and several others [16–19]. Two node model approaches have been used where the two node design was applied to multi-segments [20–23]. Multi-node models are essentially expanded versions of the twonode methods with additional shells or layers within them where the heat balance is

**49**

*Modeling Thermoregulatory Responses to Cold Environments*

calculated for each layer. Multi-node models, with both single- and multi-segment designs have become the more prevalent approach. The first multi-node model was developed by Crosbie et al. [24] and has been followed by many since [25–29]. Notable is the work of Solwijk and Hardy [30–33], where they first introduced the concepts of temperature set points and negative feedback in a controlled theory design. Their work has been built upon by many researchers over time [34–42]. The first multi-element model was originally published in 1961 by Wissler, and later improved upon [43–45]. Additional multi-element models include work by Smith [46], with the first three-dimensional (3D) transient multi-element model. As computation methods improved, a series of improvements has led to more realistic

While the majority of these models were developed with the intent of characterizing thermoregulation in various environments; several have been designed specifically to address cold environments or thermoregulatory events that specifically address cold issues (e.g., finger, hand, foot temperatures). With the intricacies of human response to cold, studies have focused on extremities, the specific areas most subject to cold injuries. One of the first attempts was by Molnar in 1957, used a heat balance approach to study hand temperature responses to cold [51]. This work was followed by work focused on finger freezing points [52–57] and whole hand modeling [58, 59]. Specific models have also been developed of the foot [60], toes [61], and facial tissues [62, 63]. Cold survival models have been developed over time to make predictions in both open air and submerged environments [64–68].

Characterizing cold related injuries is fairly complex, as the responses to cold have higher individual variability when compared to heat related injuries. From a clinical perspective, cold related injuries can be broadly divided into three categories: frostbite, nonfreezing cold injuries, and hypothermia. In addition, each of these has varying levels of severity and subcategories associated to them.

Frostbite is below the point at which skin tissue begins to freeze. While 0°C (32°F) is traditionally considered the freezing point of water, the freezing point of skin is understood to be marginally lower due to electrolytes [69]. Observed freez-

Nonfreezing cold injuries include an array of injury events where tissue freezing has not occurred but damage occurs. The level of severity of nonfreezing injuries is determined by the temperature, duration, and wetness of the exposure to the tissue. Four of the more common specific types of nonfreezing injuries include immersion (trench) foot, chilblain, cold urticaria, and cold-induced bronchoconstriction [71]. Immersion foot is a nonfreezing injury. The foot presents swollen, the skin is red initially but as severity increases the skin becomes lower in oxygen saturation and becomes cyanotic (purple, bluish discoloration) [69, 71]. Immersion foot is most often reported after tissue have been exposed for extended periods of time to non-freezing temperatures, between 0 and 15°C (32–60°F) [71]. The term 'immersion' itself refers to when the foot is actually immersed in water when the foot is wet

Chilblain is a fairly common nonfreezing injury to the skin. It can occur during 1–5 hours of temperatures below 16°C (60°F) [69]. Cold urticaria is expressed as a quick onset of redness, swelling and itchiness of the skin in response to short-term exposure (i.e., minutes) to cold environments [71]. Cold-induced bronchoconstriction is a physiological response where an individual's airways are narrowed during

ing points range from as low as −4.8°C to as high as −0.6°C [69, 70].

within boots for sustained periods of time [69, 71].

exercise in cold environments [69, 71–73].

*DOI: http://dx.doi.org/10.5772/intechopen.81238*

and complex models [8, 47–50].

**2. Clinical definitions of cold injuries**

**Figure 1.** *Example of model designs.*

#### *Modeling Thermoregulatory Responses to Cold Environments DOI: http://dx.doi.org/10.5772/intechopen.81238*

*Autonomic Nervous System Monitoring - Heart Rate Variability*

in °C, *qp* (w/m3

tissue heat.

arterial temperature, *ρ* (kg/m3

Key work by Pennes in 1948 [5], reported measured temperatures of tissue and blood at the forearm and enabled the creation of the bioheat transfer equation. This

where *k* (w/m °C) is the tissue thermal conductivity, *T* is tissue temperature

Conceptually, heat exchange between the human and the environment was first described by Lefevre in 1911; where he characterized the human as a sphere with an internal core that exchanged heat through the shell into the environment [6]. In 1934, Burton applied Fourier's law, presenting this exchange mathematically and describing the human as one uniform cylinder in what is considered by many as the

Representation of the human in a thermoregulatory model is most often done by sectioning the human into nodes, segments, and elements; typically using one of four different designs, (1) one-node, (2) two-node, (3) multi-node, or (4) multi-element [8]. An example of the difference between these designs is shown in **Figure 1**; while the multi-element approach is more realistic human shape (e.g., finite analysis distribution). Typically each node represents an independent layer with unique thermal properties, each segment represents a section or grouped section of an area of the body, and each element represents multiple thermal components that make up the whole body (often more geometrically accurate to the shape of the human).

One node models are essentially empirically derived and do not include elements within the thermoregulatory response system. There are several one node thermoregulatory models that have been used extensively over time to predict core body

Simple two-node models describe specific thermodynamic responses of a single segment, typically separated into concentric core and shell nodes. They have often been used examine thermal discomfort and physiological responses, to include the work by Gagge and Nishi [13–15], and several others [16–19]. Two node model approaches have been used where the two node design was applied to multi-segments [20–23]. Multi-node models are essentially expanded versions of the twonode methods with additional shells or layers within them where the heat balance is

is local tissue blood perfusion rate, *Cb* (J/kg/°C) is specific blood heat, *Ta* (°C) is

\_\_\_ ∂*T*

) is the tissue density, and *cp* (J/kg/°C) is the specific

) is metabolism, *W* (kg/m3

<sup>∂</sup>*<sup>t</sup>* ) (2)

/s)

equation has proven to be a key underlying basis of future models, seen as:

∇ ∙ *k* ∇*T* + *qp* + *qm* − *WCb*(*T* − *Ta*) = ρ *cp*(

) is energy deposition rate, *qm* (w/m3

first visual conceptualization of human thermoregulatory modeling [7].

temperature and thermal discomfort within a given environment [9–12].

**48**

**Figure 1.**

*Example of model designs.*

calculated for each layer. Multi-node models, with both single- and multi-segment designs have become the more prevalent approach. The first multi-node model was developed by Crosbie et al. [24] and has been followed by many since [25–29]. Notable is the work of Solwijk and Hardy [30–33], where they first introduced the concepts of temperature set points and negative feedback in a controlled theory design. Their work has been built upon by many researchers over time [34–42]. The first multi-element model was originally published in 1961 by Wissler, and later improved upon [43–45]. Additional multi-element models include work by Smith [46], with the first three-dimensional (3D) transient multi-element model. As computation methods improved, a series of improvements has led to more realistic and complex models [8, 47–50].

While the majority of these models were developed with the intent of characterizing thermoregulation in various environments; several have been designed specifically to address cold environments or thermoregulatory events that specifically address cold issues (e.g., finger, hand, foot temperatures). With the intricacies of human response to cold, studies have focused on extremities, the specific areas most subject to cold injuries. One of the first attempts was by Molnar in 1957, used a heat balance approach to study hand temperature responses to cold [51]. This work was followed by work focused on finger freezing points [52–57] and whole hand modeling [58, 59]. Specific models have also been developed of the foot [60], toes [61], and facial tissues [62, 63]. Cold survival models have been developed over time to make predictions in both open air and submerged environments [64–68].

#### **2. Clinical definitions of cold injuries**

Characterizing cold related injuries is fairly complex, as the responses to cold have higher individual variability when compared to heat related injuries. From a clinical perspective, cold related injuries can be broadly divided into three categories: frostbite, nonfreezing cold injuries, and hypothermia. In addition, each of these has varying levels of severity and subcategories associated to them.

Frostbite is below the point at which skin tissue begins to freeze. While 0°C (32°F) is traditionally considered the freezing point of water, the freezing point of skin is understood to be marginally lower due to electrolytes [69]. Observed freezing points range from as low as −4.8°C to as high as −0.6°C [69, 70].

Nonfreezing cold injuries include an array of injury events where tissue freezing has not occurred but damage occurs. The level of severity of nonfreezing injuries is determined by the temperature, duration, and wetness of the exposure to the tissue. Four of the more common specific types of nonfreezing injuries include immersion (trench) foot, chilblain, cold urticaria, and cold-induced bronchoconstriction [71].

Immersion foot is a nonfreezing injury. The foot presents swollen, the skin is red initially but as severity increases the skin becomes lower in oxygen saturation and becomes cyanotic (purple, bluish discoloration) [69, 71]. Immersion foot is most often reported after tissue have been exposed for extended periods of time to non-freezing temperatures, between 0 and 15°C (32–60°F) [71]. The term 'immersion' itself refers to when the foot is actually immersed in water when the foot is wet within boots for sustained periods of time [69, 71].

Chilblain is a fairly common nonfreezing injury to the skin. It can occur during 1–5 hours of temperatures below 16°C (60°F) [69]. Cold urticaria is expressed as a quick onset of redness, swelling and itchiness of the skin in response to short-term exposure (i.e., minutes) to cold environments [71]. Cold-induced bronchoconstriction is a physiological response where an individual's airways are narrowed during exercise in cold environments [69, 71–73].


#### **Figure 2.**

*The range of human core temperatures and associated physiological responses [76].*

Hypothermia is a broad category of cold injury and is clinically described to be the point at which core body temperature has dropped below 35°C (95°F) [74]. However, hypothermia is more specifically defined with four levels of severity; where normothermia (normal temperature level) is approximately 37°C (98.6°F), mild hypothermia is between 91.4–95°C (33–35°F), moderate hypothermia being 85.2–89.6°C (29–32°F), and severe hypothermia being 56.7–82.4°C (13.7–28°F) [69, 71]. **Figure 2** outlines specific core temperature reference points associated with physiological responses using work by Castellani et al. [69] and Pozos and Danzl [74] and described in Army Guidance [75].

#### **3. Basics of thermophysiology**

The human body is capable of maintaining thermal balance while operating within a wide range of temperatures. The human system generally maintains an

**51**

surface area to mass ratio.

*Modeling Thermoregulatory Responses to Cold Environments*

internal core temperature (Tc) of approximately 37°C. Due to natural circadian rhythm, Tc fluctuates ~0.5°C daily. However, Tc can fluctuate based on physical activity or environmental conditions, and may range from 36.0–40.0°C. The microenvironment created between human skin and clothing typically must remain within 28–30°C to maintain thermal homeostasis at rest [45]. This microenvironment changes significantly with physical activity due to metabolic heat production

Humans have an internal control system, primarily the preoptic area of the anterior hypothalamus, responsible for maintaining healthy body temperature. The hypothalamus uses feedback from two main sources, the skin and the blood. When temperature changes (hot or cold) are identified by either of these two sources, impulses are sent to the hypothalamus which in turn directs physiological changes to compensate for these temperatures. To protect from cold or heat injury, the human body attempts to either generate or dissipate heat to stay warm or cool off. Heat production is a natural process for humans and is a function of metabolism, oxidation of foods, and muscular activity. Heat transfer between the human and environment occurs via four pathways: conduction, convection, radiation, and evaporation. This heat exchange process is typically referred to as heat or thermal

where S is heat storage; M is metabolic rate; W is work rate; R is radiation; C is convection; K is conduction; and E is evaporation. Radiation is heat that is transferred via electromagnetic waves (e.g., solar radiation). Conduction is heat transfer due to the body's direct contact with a solid object (e.g., touching a cold surface). Convection is heat transfer between the body and a fluid such as air or water. Evaporation is heat loss to the environment due to the phase change from liquid to vapor, typically associated with evaporation of sweat and respiratory water.

Hyperthermia is when heat gain exceeds heat loss; while hypothermia occurs when body temperature drops below normal levels as heat production is inadequate

Vasoconstriction and vasodilation are the two key physiological responses

Vasoconstriction is the constriction of blood vessels and occurs in response to cold environments to reduce the amount of blood flow to the skin. Vasoconstriction protects the internal organs from cold exposure but increases cold injury risk in the extremities due to lower blood flow and lower skin temperatures. Vasoconstriction in effect creates a two-layer distribution of body temperature; a cold outer shell surrounding a warmer core. The colder outer shell reduces heat loss to the environment by reducing the temperature gradient between the skin surface and the environ-

Vasodilation is essentially the opposite of vasoconstriction; where blood vessels open to allow increased blood flow across the body and out to the extremities to enable increased heat dissipation [78, 79]. During these responses, there are other associated physiological responses that help compensate for the increased skin

The extremities are more affected by cold exposure than other parts of the body.

When the human body cools, blood flow is reduced to the extremities (i.e., the hands and feet) decreasing the amount of warm blood flowing to these areas. It is a challenge to protect the hands and feet as they have lower metabolic heat production of the hands and feet due to their inherently small muscle mass and large

of how heat transfer is regulated from the body to the periphery [78, 79].

] (3)

energy balance, and can be described in the heat balance equation:

*S* = *M* ± *W* ± *R* ± *C* ± *K* − *E* [W/m2

to compensate for the rate of heat loss to the environment [77].

ment, and a colder surface radiates less heat.

blood flow (e.g., increased heart rate and cardiac output).

*DOI: http://dx.doi.org/10.5772/intechopen.81238*

and air movement.

#### *Modeling Thermoregulatory Responses to Cold Environments DOI: http://dx.doi.org/10.5772/intechopen.81238*

*Autonomic Nervous System Monitoring - Heart Rate Variability*

Hypothermia is a broad category of cold injury and is clinically described to be the point at which core body temperature has dropped below 35°C (95°F) [74]. However, hypothermia is more specifically defined with four levels of severity; where normothermia (normal temperature level) is approximately 37°C (98.6°F), mild hypothermia is between 91.4–95°C (33–35°F), moderate hypothermia being 85.2–89.6°C (29–32°F), and severe hypothermia being 56.7–82.4°C (13.7–28°F) [69, 71]. **Figure 2** outlines specific core temperature reference points associated with physiological responses using work by Castellani et al. [69] and Pozos and

The human body is capable of maintaining thermal balance while operating within a wide range of temperatures. The human system generally maintains an

Danzl [74] and described in Army Guidance [75].

*The range of human core temperatures and associated physiological responses [76].*

**3. Basics of thermophysiology**

**50**

**Figure 2.**

internal core temperature (Tc) of approximately 37°C. Due to natural circadian rhythm, Tc fluctuates ~0.5°C daily. However, Tc can fluctuate based on physical activity or environmental conditions, and may range from 36.0–40.0°C. The microenvironment created between human skin and clothing typically must remain within 28–30°C to maintain thermal homeostasis at rest [45]. This microenvironment changes significantly with physical activity due to metabolic heat production and air movement.

Humans have an internal control system, primarily the preoptic area of the anterior hypothalamus, responsible for maintaining healthy body temperature. The hypothalamus uses feedback from two main sources, the skin and the blood. When temperature changes (hot or cold) are identified by either of these two sources, impulses are sent to the hypothalamus which in turn directs physiological changes to compensate for these temperatures. To protect from cold or heat injury, the human body attempts to either generate or dissipate heat to stay warm or cool off. Heat production is a natural process for humans and is a function of metabolism, oxidation of foods, and muscular activity. Heat transfer between the human and environment occurs via four pathways: conduction, convection, radiation, and evaporation. This heat exchange process is typically referred to as heat or thermal energy balance, and can be described in the heat balance equation:

$$\mathbf{S} = \begin{array}{c} \mathbf{M} \neq \mathbf{W} \neq \mathbf{R} \neq \mathbf{C} \neq \mathbf{K} - E \begin{bmatrix} \mathbf{W}/\mathbf{m}^2 \end{bmatrix} \tag{3}$$

where S is heat storage; M is metabolic rate; W is work rate; R is radiation; C is convection; K is conduction; and E is evaporation. Radiation is heat that is transferred via electromagnetic waves (e.g., solar radiation). Conduction is heat transfer due to the body's direct contact with a solid object (e.g., touching a cold surface). Convection is heat transfer between the body and a fluid such as air or water. Evaporation is heat loss to the environment due to the phase change from liquid to vapor, typically associated with evaporation of sweat and respiratory water.

Hyperthermia is when heat gain exceeds heat loss; while hypothermia occurs when body temperature drops below normal levels as heat production is inadequate to compensate for the rate of heat loss to the environment [77].

Vasoconstriction and vasodilation are the two key physiological responses of how heat transfer is regulated from the body to the periphery [78, 79]. Vasoconstriction is the constriction of blood vessels and occurs in response to cold environments to reduce the amount of blood flow to the skin. Vasoconstriction protects the internal organs from cold exposure but increases cold injury risk in the extremities due to lower blood flow and lower skin temperatures. Vasoconstriction in effect creates a two-layer distribution of body temperature; a cold outer shell surrounding a warmer core. The colder outer shell reduces heat loss to the environment by reducing the temperature gradient between the skin surface and the environment, and a colder surface radiates less heat.

Vasodilation is essentially the opposite of vasoconstriction; where blood vessels open to allow increased blood flow across the body and out to the extremities to enable increased heat dissipation [78, 79]. During these responses, there are other associated physiological responses that help compensate for the increased skin blood flow (e.g., increased heart rate and cardiac output).

The extremities are more affected by cold exposure than other parts of the body. When the human body cools, blood flow is reduced to the extremities (i.e., the hands and feet) decreasing the amount of warm blood flowing to these areas. It is a challenge to protect the hands and feet as they have lower metabolic heat production of the hands and feet due to their inherently small muscle mass and large surface area to mass ratio.

**Figure 3.** *Peripheral (skin) and core temperature influence on central nervous system (CNS) and physiological outcomes.*

From a functional perspective, the balance of control within the human system depends on the response to cold exposure and interaction between peripheral (skin) and core body temperatures with the central nervous system (CNS) and the various physiological responses (**Figure 3**); [74].

#### **4. Importance of clothing**

Clothing has long been used to provide protection from environmental elements (heat, cold, etc.) or physical or biological hazards (e.g., rocks, thorns). Clothing properties and requirements vary widely among users and use cases. A single clothing ensemble cannot protect an individual from the extremes of the temperature spectrum of earth, being approximately −89°C at its coldest and 58°C at its warmest. However, clothing is a toll to protect each end of this spectrum of environmental extremes [80]. However, protections must be based on use cases to achieve the desired thermal comfort. For example, protective equipment for American football players (i.e., pads and helmet) is vastly different than protective equipment worn by soldiers (i.e., body armor, ballistic helmet). It should be noted that added protection may increase the thermal burden to wearers, and thus increases risk of heat injuries [81–83].

It is critical to understand the clothing option tradespace in order to predict and prepare for the impact clothing has on protecting or impairing human health. That is to say, the selection of the proper clothing, requires an understanding of how the human (physiology, anthropology, etc.), the anticipated activities (i.e., work rate, length of exposure and metabolic heat production), the work environments (temperature, humidity, etc.), and the biophysical properties of clothing worn (heat transfer performance) will interact in each workplace scenario.

**53**

*Modeling Thermoregulatory Responses to Cold Environments*

Clothing protects the wearer from environmental threats, but may impose a level of thermal burden. Both the biophysical resistances (thermal and evaporative) and spectrophotometric (reflectance, absorptivity, and transmittance) properties of clothing can have a significant influence on the impact of the environment on the wearer. Measurements of the biophysical properties of clothing can be used to model the impacts on thermal sensation (e.g., thermal comfort) and thermoregulatory responses (e.g., heat strain, cold protection). The thermal and evaporative resistances, wind effects, and spectrophotometric properties of the clothing are

Sweating thermal manikins have long been used to provide biophysical measures of clothing and equipment worn by the human [84]. While direct biophysical comparisons can be helpful, i.e., comparing one ensemble's value to another [85], a more informative approach is to combine these measured values with thermoregulatory modeling. Models enable the prediction of thermoregulatory responses based on different individuals, as well as varied environments, clothing, or activity levels. The current standard for thermal manikin testing calls for two fundamental measures: thermal resistance (*Rt*) [86] and evaporative resistance (*Ret*) [87]. These two measures represent the dry heat exchange (*Rt*: convection, conduction, and radiation) and wet heat exchange (*Ret*: evaporation). After converting both *Rt* and *Ret* into units of clo and im [88, 89], a ratio can be used to describe an ensemble's

Each ensemble should be tested using chamber conditions from the American Society for Testing and Materials (ASTM) standards for assessing *Rt* (ASTM F1291-

Thermal resistance (*Rt*) is the dry heat transfer from the surface of the manikin

where Ts is surface temperature and Ta is the air temperature, both in °C or °K. Q is power input (W) to maintain the surface (skin) temperature (Ts) of the manikin

1 *clo* = 6.45(*IT*) (5)

*American Society for Testing and Materials standard chamber and manikin conditions for testing thermal (Rt)* 

**Ambient temperature (***Ta***, °C)**

*<sup>Q</sup>*/*<sup>A</sup>* [m2K/W] (4)

**Relative humidity (RH, %)**

35 20 50 0.4 0

35 35 40 0.4 100

. These measures

**Saturation (%)**

**Wind velocity (***V***, ms<sup>−</sup><sup>1</sup> )**

through the clothing and into the environment, mainly from convection, and

at a given set point; A is the surface area of the measurement in m<sup>2</sup>

*DOI: http://dx.doi.org/10.5772/intechopen.81238*

critical measurements for this purpose.

*4.1.1 Thermal and evaporative resistance*

evaporative potential (im/clo) [90].

described as:

**Variable (unit)**

*Rt* (m2 K/W)

*Ret* (m2 Pa/W)

*and evaporative (Ret) resistance.*

**Table 1.**

16) and *Ret* (ASTM F2370-16) [86, 87] (**Table 1**).

*Rt* <sup>=</sup> (*Ts* <sup>−</sup> *Ta*) \_\_\_\_\_\_\_

of *Rt* can then be converted to units of clo:

**Skin/surface temperature (***Ts***, °C)**

**4.1 Clothing biophysics**

#### **4.1 Clothing biophysics**

*Autonomic Nervous System Monitoring - Heart Rate Variability*

From a functional perspective, the balance of control within the human system depends on the response to cold exposure and interaction between peripheral (skin) and core body temperatures with the central nervous system (CNS) and the various

*Peripheral (skin) and core temperature influence on central nervous system (CNS) and physiological outcomes.*

Clothing has long been used to provide protection from environmental elements (heat, cold, etc.) or physical or biological hazards (e.g., rocks, thorns). Clothing properties and requirements vary widely among users and use cases. A single clothing ensemble cannot protect an individual from the extremes of the temperature spectrum of earth, being approximately −89°C at its coldest and 58°C at its warmest. However, clothing is a toll to protect each end of this spectrum of environmental extremes [80]. However, protections must be based on use cases to achieve the desired thermal comfort. For example, protective equipment for American football players (i.e., pads and helmet) is vastly different than protective equipment worn by soldiers (i.e., body armor, ballistic helmet). It should be noted that added protection may increase the

It is critical to understand the clothing option tradespace in order to predict and prepare for the impact clothing has on protecting or impairing human health. That is to say, the selection of the proper clothing, requires an understanding of how the human (physiology, anthropology, etc.), the anticipated activities (i.e., work rate, length of exposure and metabolic heat production), the work environments (temperature, humidity, etc.), and the biophysical properties of clothing worn (heat

thermal burden to wearers, and thus increases risk of heat injuries [81–83].

transfer performance) will interact in each workplace scenario.

physiological responses (**Figure 3**); [74].

**4. Importance of clothing**

**Figure 3.**

**52**

Clothing protects the wearer from environmental threats, but may impose a level of thermal burden. Both the biophysical resistances (thermal and evaporative) and spectrophotometric (reflectance, absorptivity, and transmittance) properties of clothing can have a significant influence on the impact of the environment on the wearer. Measurements of the biophysical properties of clothing can be used to model the impacts on thermal sensation (e.g., thermal comfort) and thermoregulatory responses (e.g., heat strain, cold protection). The thermal and evaporative resistances, wind effects, and spectrophotometric properties of the clothing are critical measurements for this purpose.

#### *4.1.1 Thermal and evaporative resistance*

Sweating thermal manikins have long been used to provide biophysical measures of clothing and equipment worn by the human [84]. While direct biophysical comparisons can be helpful, i.e., comparing one ensemble's value to another [85], a more informative approach is to combine these measured values with thermoregulatory modeling. Models enable the prediction of thermoregulatory responses based on different individuals, as well as varied environments, clothing, or activity levels.

The current standard for thermal manikin testing calls for two fundamental measures: thermal resistance (*Rt*) [86] and evaporative resistance (*Ret*) [87]. These two measures represent the dry heat exchange (*Rt*: convection, conduction, and radiation) and wet heat exchange (*Ret*: evaporation). After converting both *Rt* and *Ret* into units of clo and im [88, 89], a ratio can be used to describe an ensemble's evaporative potential (im/clo) [90].

Each ensemble should be tested using chamber conditions from the American Society for Testing and Materials (ASTM) standards for assessing *Rt* (ASTM F1291- 16) and *Ret* (ASTM F2370-16) [86, 87] (**Table 1**).

Thermal resistance (*Rt*) is the dry heat transfer from the surface of the manikin through the clothing and into the environment, mainly from convection, and described as:

$$R\_t = \frac{\left(T\_s - T\_a\right)}{Q/A} \left[\text{m}^2 \,\text{K}/\text{W}\right] \tag{4}$$

where Ts is surface temperature and Ta is the air temperature, both in °C or °K. Q is power input (W) to maintain the surface (skin) temperature (Ts) of the manikin at a given set point; A is the surface area of the measurement in m<sup>2</sup> . These measures of *Rt* can then be converted to units of clo:

$$\mathbf{1}\,clos\,\,=\,\,\mathbf{6}.\,\mathbf{45}(I\_T)\,\tag{5}$$


**Table 1.**

*American Society for Testing and Materials standard chamber and manikin conditions for testing thermal (Rt) and evaporative (Ret) resistance.*

where IT is the total insulation including boundary air layers. Evaporative resistance (Ret) is heat loss from the body in isothermal conditions (Ts ≈ Ta), described as:

$$R\_{\text{et}} = \frac{(P\_{\text{sat}} - P\_d)}{Q/A} [\text{m}^2 \text{Pa/W}] \tag{6}$$

where Psat is vapor pressure in Pascal at the surface of the manikin (assumed to be fully saturated), and Pa is ambient vapor pressure, in Pascal, of the chamber environment. Measures of Ret can then be converted to a vapor permeability index (im), a non-dimensional measure of water vapor resistance of materials defined as:

$$\dot{i}\_m = \frac{60.6515 \frac{Pd}{t} R\_t}{C} \tag{7}$$

#### *4.1.2 Wind effects on thermal and evaporative resistance*

In order to use the biophysical measures, i.e., measures of *Rt* (clo) and *Ret* (im) for thermoregulatory modeling there is a need to first estimate the effects of wind velocity on the biophysical characteristics of the ensemble (i.e., to determine how wind affects clo and im values). These effects are typically referred to as wind velocity coefficients or gamma values (<sup>g</sup> ) [91]. Historically, these coefficients were determined by collecting measurements of both *Rt* and *Ret* at multiple wind velocities above the ASTM standard of 0.4 m/s. However, recent work suggests these coefficient values can be accurately estimated from single wind velocity tests [91, 92].

Clothing properties and wind coefficients are critical inputs to a number of predictive mathematical models [10, 11, 93, 94], as they use these values to describe wind-related effects, such as intrinsic insulation (*Icl*) and intrinsic permeability index (*icl*) for either the whole body or segments of the body, as seen with:

$$I\_{cl} = \quad I\_t - \begin{pmatrix} I\_a \\ \overline{f\_d} \end{pmatrix} \tag{8}$$

where *Ia* is insulation measured on a nude thermal manikin, *It* is total insulation, and (*fcl*) is clothing area factor, calculated by:

$$f\_d = \frac{A}{A\_d} \tag{9}$$

where *A* (m<sup>2</sup> ) is surface area of the nude manikin, and *Acl* (m2 ) is surface area the clothed manikin.

True measures of *Acl* require a three-dimensional scan. However, methods for estimating *Acl* have been derived by McCullough et al. [95]. Simplified or estimated *Acl* and *fcl* is often used where a value of 1 is assumed for warm-weather or indoor clothing. For cold-weather clothing a value would be calculated from:

$$f\_d = \mathbf{1.0} \mathbf{+0.3} \cdot I\_d \tag{10}$$

**55**

*Modeling Thermoregulatory Responses to Cold Environments*

responses and injury outcomes in cold environments due to wind chill effects [69, 98, 99]. There has been work to develop that relates exposure time to predicted injury (e.g., frostbite) likely to occur due to temperature and levels of wind speed

Mathematical models can predict the human thermal response (e.g., metabolic heat production, core body temperature (*Tc*), endurance time) resulting from activity, environment, and clothing. These mathematical models are typically binned into one of three categories, either as rational, empirical, or hybrid. Rational (mechanistic) models mathematically represent phenomena based on an understanding of physics and physiology (biology, chemistry, physics). Empirical models mathematically reflect the observed relationship among experimental data. While both methods, rational and empirical, are scientifically valid approaches, perhaps the most effective approach is the hybrid or mixed model method that uses

Rational modeling incorporates equations that describe heat balance and thermoregulatory processes [100]. Two fundamental equations are used to describe internal heat balance and for heat exchange between skin and environment. One equation outlines the temperature gradient change from core to skin and can be seen as:

T is the tissue temperature (°C), t is time (sec), qm is metabolic heat production rate

for heat conduction based on the tissue temperature gradient, ωbl is blood flow rate

The second equation describes heat exchange from the skin surface to the

(°C), *n* is the tissue coordinate normal to the skin surface; while the balance is the

tory actions such as sweating, vasodilation, vasoconstriction, and shivering.

(grossly consisting of core, muscle, fat, and skin) along with clothing and air layers within clothing is only the first step to modeling the human's response in a given environment. **Figure 4** shows the rational basis behind the SCENARIO model where the human is mathematically represented as one multi-layer cylinder, based on the relationship of the layers of the human, their respective physiological

Rational models of thermoregulatory processes usually include equations for the controlling signals of the thermoregulation system and equations for thermoregula-

Understanding the interplay between each of the different layers of the human

T + ωbl ∙ ρbl cbl ∙ (Tbl − T) [W m−3] (11)

 °C<sup>−</sup><sup>1</sup> ),

is a Laplace transform

), cbl is the blood specific heat (kJ

), T is tissue temperature

), c is the specific heat of the tissue (kJ kg<sup>−</sup><sup>1</sup>

∂n <sup>=</sup> <sup>R</sup> <sup>+</sup> <sup>C</sup> <sup>+</sup> <sup>K</sup> <sup>+</sup> <sup>E</sup> [W <sup>m</sup>−2] (12)

): R is radiative, C is convective, K is

°C<sup>−</sup><sup>1</sup>

), ∇<sup>2</sup>

°C<sup>−</sup><sup>1</sup>

**5. Modeling risk and predicting heat and cold related injuries**

*DOI: http://dx.doi.org/10.5772/intechopen.81238*

exposure [98].

a combination of the two.

ρc ∙ \_\_\_

(W m<sup>−</sup><sup>3</sup>

environment as:

(m3 s<sup>−</sup><sup>1</sup> m<sup>−</sup><sup>3</sup>

kg<sup>−</sup><sup>1</sup> °C<sup>−</sup><sup>1</sup> ∂T

where ρ is tissue mass (kg m<sup>−</sup><sup>3</sup>

−λ ∙ \_\_\_

conductive, and E is evaporative.

responses, and clothing [93, 94].

array of avenues of heat exchange (W m<sup>−</sup><sup>2</sup>

∂t <sup>=</sup> qm <sup>+</sup> <sup>λ</sup> <sup>∙</sup> <sup>∇</sup><sup>2</sup>

), λ is the tissue heat conductivity (W m<sup>−</sup><sup>1</sup>

), and Tbl is the blood temperature (°C).

tissue), ρbl is blood flow mass (kg m<sup>−</sup><sup>3</sup>

∂T

where λ is the tissue heat conductivity (W m<sup>−</sup><sup>1</sup>

**5.1 Rational models**

While these estimation methods have been studied and produce acceptable variance between estimated and direct measured results [96], there are questions whether estimates remain acceptable for clothing insulation outside typical cold weather clothing insulation ranges, e.g., 0.2–1.7 clo [97].

Most clothing-based thermal models, by design, predict human thermoregulatory responses to various environmental conditions and therefore require quantitative insights into the change in clothing properties with changes in wind velocity. Furthermore, elements of wind can significantly influence physiological responses and injury outcomes in cold environments due to wind chill effects [69, 98, 99]. There has been work to develop that relates exposure time to predicted injury (e.g., frostbite) likely to occur due to temperature and levels of wind speed exposure [98].

#### **5. Modeling risk and predicting heat and cold related injuries**

Mathematical models can predict the human thermal response (e.g., metabolic heat production, core body temperature (*Tc*), endurance time) resulting from activity, environment, and clothing. These mathematical models are typically binned into one of three categories, either as rational, empirical, or hybrid. Rational (mechanistic) models mathematically represent phenomena based on an understanding of physics and physiology (biology, chemistry, physics). Empirical models mathematically reflect the observed relationship among experimental data. While both methods, rational and empirical, are scientifically valid approaches, perhaps the most effective approach is the hybrid or mixed model method that uses a combination of the two.

#### **5.1 Rational models**

*Autonomic Nervous System Monitoring - Heart Rate Variability*

*Ret* <sup>=</sup> (*Psat* <sup>−</sup> *Pa*) \_\_\_\_\_\_\_

*im* =

velocity coefficients or gamma values (<sup>g</sup>

*Icl* <sup>=</sup> *It* <sup>−</sup> (

*fcl* = \_\_\_ *<sup>A</sup>*

and (*fcl*) is clothing area factor, calculated by:

where *A* (m<sup>2</sup>

the clothed manikin.

*4.1.2 Wind effects on thermal and evaporative resistance*

where IT is the total insulation including boundary air layers. Evaporative resistance (Ret) is heat loss from the body in isothermal conditions (Ts ≈ Ta), described as:

where Psat is vapor pressure in Pascal at the surface of the manikin (assumed to be fully saturated), and Pa is ambient vapor pressure, in Pascal, of the chamber environment. Measures of Ret can then be converted to a vapor permeability index (im), a non-dimensional measure of water vapor resistance of materials defined as:

> 60.6515 \_\_\_ *Pa* ° *C Rt*

In order to use the biophysical measures, i.e., measures of *Rt* (clo) and *Ret* (im) for thermoregulatory modeling there is a need to first estimate the effects of wind velocity on the biophysical characteristics of the ensemble (i.e., to determine how wind affects clo and im values). These effects are typically referred to as wind

determined by collecting measurements of both *Rt* and *Ret* at multiple wind velocities above the ASTM standard of 0.4 m/s. However, recent work suggests these coefficient values can be accurately estimated from single wind velocity tests [91, 92]. Clothing properties and wind coefficients are critical inputs to a number of predictive mathematical models [10, 11, 93, 94], as they use these values to describe wind-related effects, such as intrinsic insulation (*Icl*) and intrinsic permeability index (*icl*) for either the whole body or segments of the body, as seen with:

> \_\_ *Ia*

where *Ia* is insulation measured on a nude thermal manikin, *It* is total insulation,

*Acl*

) is surface area of the nude manikin, and *Acl* (m2

clothing. For cold-weather clothing a value would be calculated from:

weather clothing insulation ranges, e.g., 0.2–1.7 clo [97].

True measures of *Acl* require a three-dimensional scan. However, methods for estimating *Acl* have been derived by McCullough et al. [95]. Simplified or estimated *Acl* and *fcl* is often used where a value of 1 is assumed for warm-weather or indoor

*fcl* = 1.0 + 0.3 ∙ *Icl* (10)

While these estimation methods have been studied and produce acceptable variance between estimated and direct measured results [96], there are questions whether estimates remain acceptable for clothing insulation outside typical cold

Most clothing-based thermal models, by design, predict human thermoregulatory responses to various environmental conditions and therefore require quantitative insights into the change in clothing properties with changes in wind velocity. Furthermore, elements of wind can significantly influence physiological

\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ *Ret*

*<sup>Q</sup>*/*<sup>A</sup>* [m2Pa/W] (6)

(7)

) [91]. Historically, these coefficients were

*fcl*) (8)

(9)

) is surface area

**54**

Rational modeling incorporates equations that describe heat balance and thermoregulatory processes [100]. Two fundamental equations are used to describe internal heat balance and for heat exchange between skin and environment. One equation outlines the temperature gradient change from core to skin and can be seen as:

$$\rho \mathbf{c} \cdot \frac{\partial \mathbf{T}}{\partial \mathbf{t}} = \mathbf{q}\_{\mathrm{m}} + \boldsymbol{\lambda} \cdot \nabla^{2} \mathbf{T} + \alpha \mathbf{o}\_{\mathrm{bl}} \cdot \rho\_{\mathrm{bl}} \mathbf{c}\_{\mathrm{bl}} \cdot \left(\mathbf{T}\_{\mathrm{bl}} - \mathbf{T}\right) \left[\mathbf{W} \,\mathrm{m}^{-3}\right] \tag{11}$$

where ρ is tissue mass (kg m<sup>−</sup><sup>3</sup> ), c is the specific heat of the tissue (kJ kg<sup>−</sup><sup>1</sup> °C<sup>−</sup><sup>1</sup> ), T is the tissue temperature (°C), t is time (sec), qm is metabolic heat production rate (W m<sup>−</sup><sup>3</sup> ), λ is the tissue heat conductivity (W m<sup>−</sup><sup>1</sup> °C<sup>−</sup><sup>1</sup> ), ∇<sup>2</sup> is a Laplace transform for heat conduction based on the tissue temperature gradient, ωbl is blood flow rate (m3 s<sup>−</sup><sup>1</sup> m<sup>−</sup><sup>3</sup> tissue), ρbl is blood flow mass (kg m<sup>−</sup><sup>3</sup> ), cbl is the blood specific heat (kJ kg<sup>−</sup><sup>1</sup> °C<sup>−</sup><sup>1</sup> ), and Tbl is the blood temperature (°C).

The second equation describes heat exchange from the skin surface to the environment as:

$$-\lambda \cdot \frac{\partial \mathbf{T}}{\partial \mathbf{n}} = \mathbf{R} + \mathbf{C} + \mathbf{K} + \mathbf{E} \left[ \mathbf{W} \,\mathbf{m}^{-2} \right] \tag{12}$$

where λ is the tissue heat conductivity (W m<sup>−</sup><sup>1</sup> °C<sup>−</sup><sup>1</sup> ), T is tissue temperature (°C), *n* is the tissue coordinate normal to the skin surface; while the balance is the array of avenues of heat exchange (W m<sup>−</sup><sup>2</sup> ): R is radiative, C is convective, K is conductive, and E is evaporative.

Rational models of thermoregulatory processes usually include equations for the controlling signals of the thermoregulation system and equations for thermoregulatory actions such as sweating, vasodilation, vasoconstriction, and shivering.

Understanding the interplay between each of the different layers of the human (grossly consisting of core, muscle, fat, and skin) along with clothing and air layers within clothing is only the first step to modeling the human's response in a given environment. **Figure 4** shows the rational basis behind the SCENARIO model where the human is mathematically represented as one multi-layer cylinder, based on the relationship of the layers of the human, their respective physiological responses, and clothing [93, 94].

**Figure 4.**

*Fundamental rational basis (SCENARIO model) [93], reused with permission. Note: BFcr is core blood flow, BFmu is muscle blood flow, BFfat is muscle blood flow, BFsk is skin blood flow.*

#### **5.2 Empirical models**

Empirical models are mathematical representations of data, often using statistical methods such as regression or correlational analysis. An example model is the Heat Strain Decision Aid (HSDA), empirically derived by the U.S. Army from an extensive database of human studies that incorporates the biophysics of heat exchange [10, 11, 101] and predicts core temperature, maximum work times, sustainable work-rest cycles, water requirements, and the estimated likelihood of heat casualties. This model has been used to derive guidance and doctrine for military [102] and fluid intake guidance for the public [103]. The basis of HSDA includes both principles of heat exchange along with empirical predictions of physiological responses. Collectively 16 inputs from four elements (individual characteristics, physical activity, clothing biophysics, and environmental conditions) are used to mathematically predict the rise in core body temperature during physical activity [10].

#### **5.3 Simple models**

Originally developed by Holmér [104], a simple calculation was adopted by the International Organization Standardization (ISO) technical report (ISO 11079) [105], as an evaluation metric of the insulation required (IREQ ) for given environments and activities to compare ensemble performance. The IREQ method functionally describes the concept for balancing the heat exchange between the human and the environment, and simplified as:

$$M - W = \begin{array}{c} E\_{\text{rxr}} + C\_{\text{rxr}} + E + K + R + C + S \end{array} \tag{13}$$

where *M* is metabolic heat produced, *W* is effective mechanical work and collectively *M-W* represents the heat produced within the human; while the opposite side of this balance, *Eres* and *Cres* represent the respiratory heat exchange (evaporative and convective), and *E, K, R,* and *C* represent the conventional heat exchange methods (evaporative, conductive, radiative, and convective) and *S* is heat storage.

The IREQ equation illustrates the rational balance between thermal insulation and heat transfer, seen as:

$$IREQ\\_=\ \frac{\overline{t}\_{sk} - t\_d}{R \star C} \tag{14}$$

**57**

**Table 2.**

*Modeling Thermoregulatory Responses to Cold Environments*

*IREQ* = \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ *<sup>t</sup>*

where *tsk* is mean skin temperature, *tcl* clothing surface temperature, and

This method also determines the minimum and neutral IREQ (IREQmin and IREQneutral), and describes amounts of insulation needed to maintain thermal balance (minimum) and to maintain an equilibrium balance (neutral). The ISO 11079 also outlines general scenarios for the minimum required insulation (IREQmin) for multiple work intensities and environments. Collectively this method provides a simple method for evaluating the effectiveness of specific cold weather clothing at protecting from cold injuries [106].

When developing a cold-based thermal model there are a number of physiological, environmental, and biophysical parameters that can and should be considered. Particular attention should be paid to the extremity temperatures blood flow and

As blood flow is a major component to the overall movement of heat, it is important to be able to predict blood flow to the muscle, skin, and distribution of blood flow to these regions within the body. **Table 2** outlines some historical methods

Shivering is where, in response to cold exposure, muscles involuntarily contract rhythmically off and on in an attempt to increase body temperature [74]. During

**Prediction Equation Units References**

*dilat* = β*dil*,1 ∙*error*<sup>1</sup> + β*dil*,2 ∙ (*warms* − *colds*) + β*dil*,3 ∙ *warm*<sup>1</sup> ∙ *warms*

*stric* = β*str*,1 ∙*error*<sup>1</sup> + β*str*,2 ∙ (*warms* − *colds*) + β*str*,3 ∙ *cold*<sup>1</sup> ∙ *colds*

Skin blood flow (*bfs*) *bfs* = 0.53 ∙ *bfforearm* − 0.83 mL min<sup>−</sup><sup>1</sup> [116]

<sup>1</sup> <sup>+</sup> <sup>γ</sup>*str* <sup>∙</sup> *stric* <sup>∙</sup> *<sup>Q</sup>*<sup>10</sup>

*Note: qs and qs,r are skin blood flow and rate; AVD is active vasodilation; CVC is cutaneous vascular conductance addition of M (mediated), L (locally), and E (effect of exercise);* β*dil and* β*str are control coefficients for vasodilation and vasoconstriction; warms and colds refer to calculated net warm and cold receptors; bf forearm is blood flow at the forearm;* γ *dil and* γ *str are distribution coefficients for vasodilation and vasoconstriction; cm is a proportionality* 

*qs* = *qs*,*<sup>r</sup>* ∙ *AVD* ∙ *CVCM* ∙ *CVCL* ∙ *CVCE* mL 100 mL

\_\_\_\_\_ *T*−*T*<sup>0</sup> tissue<sup>−</sup><sup>1</sup>

<sup>10</sup> L h<sup>−</sup><sup>1</sup> [33]

*qm* = *qm*,*<sup>r</sup>* + *cm* ∙ ∆*Mw* L h<sup>−</sup><sup>1</sup> [33]

*bfm* = 0.47 ∙ *bfforearm* + 0.83 mL min<sup>−</sup><sup>1</sup> [116]

min<sup>−</sup><sup>1</sup>

L h<sup>−</sup><sup>1</sup> [33]

L h<sup>−</sup><sup>1</sup> [33]

[79, 107–115]

¯*sk* <sup>−</sup> *tcl <sup>M</sup>* <sup>−</sup> *<sup>W</sup>* <sup>−</sup> *Eres* <sup>−</sup> *Cres* <sup>−</sup> *<sup>E</sup>* (15)

*DOI: http://dx.doi.org/10.5772/intechopen.81238*

**5.4 Key elements for model development**

used in models for predicting each of these elements.

Local blood flow (*lqs*) *lqs* <sup>=</sup> *qs*,*<sup>r</sup>* <sup>+</sup> <sup>γ</sup>*dil* <sup>∙</sup> *dilat* \_\_\_\_\_\_\_\_\_\_\_

*coefficient; and MW is metabolic heat produced from exercise.*

*Methods for predicting skin blood flow in thermoregulatory models.*

or more formally as:

*M* − *W* − *Eres* − *Cres* − *E* = *R* + *C*.

metabolic heat production.

*5.4.1 Blood flow*

*5.4.2. Shivering*

Cutaneous blood flow (*qs*)

Skin vasodilation

Skin vasoconstriction

Muscle blood flow

Muscle blood flow

(dilat)

(stric)

(*qm*)

(*bfm*)

*Modeling Thermoregulatory Responses to Cold Environments DOI: http://dx.doi.org/10.5772/intechopen.81238*

or more formally as:

*Autonomic Nervous System Monitoring - Heart Rate Variability*

*BFmu is muscle blood flow, BFfat is muscle blood flow, BFsk is skin blood flow.*

Empirical models are mathematical representations of data, often using statistical methods such as regression or correlational analysis. An example model is the Heat Strain Decision Aid (HSDA), empirically derived by the U.S. Army from an extensive database of human studies that incorporates the biophysics of heat exchange [10, 11, 101] and predicts core temperature, maximum work times, sustainable work-rest cycles, water requirements, and the estimated likelihood of heat casualties. This model has been used to derive guidance and doctrine for military [102] and fluid intake guidance for the public [103]. The basis of HSDA includes both principles of heat exchange along with empirical predictions of physiological responses. Collectively 16 inputs from four elements (individual characteristics, physical activity, clothing biophysics, and environmental conditions) are used to mathematically predict the rise in core body temperature during

*Fundamental rational basis (SCENARIO model) [93], reused with permission. Note: BFcr is core blood flow,* 

Originally developed by Holmér [104], a simple calculation was adopted by the International Organization Standardization (ISO) technical report (ISO 11079) [105], as an evaluation metric of the insulation required (IREQ ) for given environments and activities to compare ensemble performance. The IREQ method functionally describes the concept for balancing the heat exchange between the human

*M* − *W* = *Eres* + *Cres* + *E* + *K* + *R* + *C* + *S* (13)

where *M* is metabolic heat produced, *W* is effective mechanical work and collectively *M-W* represents the heat produced within the human; while the opposite side of this balance, *Eres* and *Cres* represent the respiratory heat exchange (evaporative and convective), and *E, K, R,* and *C* represent the conventional heat exchange methods (evaporative, conductive, radiative, and convective) and *S* is

The IREQ equation illustrates the rational balance between thermal insulation

*t* ¯*sk* − *tcl*

*<sup>R</sup>* <sup>+</sup> *<sup>C</sup>* (14)

**5.2 Empirical models**

**Figure 4.**

physical activity [10].

and the environment, and simplified as:

*IREQ* = \_\_\_\_\_

**5.3 Simple models**

**56**

heat storage.

and heat transfer, seen as:

or more formally as: 
$$IREQ = \frac{\overline{F}\_{ik} - t\_{il}}{M - W - E\_{res} - C\_{res} - E} \tag{15}$$

where *tsk* is mean skin temperature, *tcl* clothing surface temperature, and *M* − *W* − *Eres* − *Cres* − *E* = *R* + *C*.

This method also determines the minimum and neutral IREQ (IREQmin and IREQneutral), and describes amounts of insulation needed to maintain thermal balance (minimum) and to maintain an equilibrium balance (neutral). The ISO 11079 also outlines general scenarios for the minimum required insulation (IREQmin) for multiple work intensities and environments. Collectively this method provides a simple method for evaluating the effectiveness of specific cold weather clothing at protecting from cold injuries [106].

#### **5.4 Key elements for model development**

When developing a cold-based thermal model there are a number of physiological, environmental, and biophysical parameters that can and should be considered. Particular attention should be paid to the extremity temperatures blood flow and metabolic heat production.

#### *5.4.1 Blood flow*

As blood flow is a major component to the overall movement of heat, it is important to be able to predict blood flow to the muscle, skin, and distribution of blood flow to these regions within the body. **Table 2** outlines some historical methods used in models for predicting each of these elements.

#### *5.4.2. Shivering*

Shivering is where, in response to cold exposure, muscles involuntarily contract rhythmically off and on in an attempt to increase body temperature [74]. During


*Note: qs and qs,r are skin blood flow and rate; AVD is active vasodilation; CVC is cutaneous vascular conductance addition of M (mediated), L (locally), and E (effect of exercise);* β*dil and* β*str are control coefficients for vasodilation and vasoconstriction; warms and colds refer to calculated net warm and cold receptors; bf forearm is blood flow at the forearm;* γ *dil and* γ *str are distribution coefficients for vasodilation and vasoconstriction; cm is a proportionality coefficient; and MW is metabolic heat produced from exercise.*

#### **Table 2.**

*Methods for predicting skin blood flow in thermoregulatory models.*


*Note: T is temperature; h is head; set is set point of temperatures; Wa,m is a weighting coefficient; qs is heat flux s is skin; BMI is body mass index; ty is Tympanic membrane; re is rectal; and es is esophageal; BF% is body fat percentage.*

#### **Table 3.**

*Methods for predicting shivering related model calculations.*


*Note: G is grade (° for Ref. [125], % for others); Ht, height (inches for Ref. [129]); L, external load (kg); M, mass (kg); η, terrain factor; S, speed (mph for Ref. [129], m s<sup>−</sup><sup>1</sup> for others); VO2-rest, resting oxygen consumption (ml kg<sup>−</sup><sup>1</sup> min<sup>−</sup><sup>1</sup> ); Wt, weight (lbs).*

#### **Table 4.**

*Methods for predicting metabolic rates during walking or standing.*

cold exposure the shivering response is a critical element to model, as the production of heat protects the body core temperature despite skin to the ambient heat loss. **Table 3** outlines some of the modeling approaches that have been used to predict the shivering response as they relate to the total metabolic rate (*M*) and the heat production from shivering (*Mshiv*).

**59**

**Acknowledgements**

of this chapter.

**Conflict of interest**

*Modeling Thermoregulatory Responses to Cold Environments*

activity using the assumed basal rate of 58.2 W/m2

An individual's metabolic heat production can be estimated at rest and during

equivalents (METS) of activity; where 1 MET is resting. Ainsworth et al. [122] outlines a wide range of activities and their associated MET level for reference. However, there are metabolic rate estimation methods available based on energy costs of standing or walking (**Table 4**). Recently work has also been published that makes corrections to some of these prediction methods specific to traveling over snow terrain [123].

Mathematical models and decision aids are tools for inspiring advancements within the field of thermophysiology, and for providing solutions to help mitigate

Scientifically based models have been used in the development of public [97, 98, 103, 104, 130–132] and military guidance [75, 131, 133], for forensic assessments [134–140], as well in the creation of operational tools for survival [141, 142]. Notably, the use of Xu and Werner's six cylinder model [41] was used to develop the Probability of Survival Decision Aid (PSDA), a computer model used to predict hypothermia and dehydration impact on functional time (i.e., duration of ability for useful work), and survival time while exposed to marine environments [67, 143, 144]. The PSDA model is underpinned by the rational principles described herein and the outputs are provided in a customized graphical user interface. This tool has been transitioned for use by Search and Rescue (SaR) personnel and continues to be

refined and verified based on real-world feedback and data collected [144].

There is a need for continued advancement in the development of individualized modeling methods such as finite element models as well as providing models and decision aids that can be used in dynamic settings and for complex scenarios with prolonged durations. Additionally, inclusion of probabilistic and statistically based risk factors should be used as elements that help improve individualized predictions. The accessibility of the information from these tools continues to be a challenge for the scientific community. While providing usable information to the public, military, and other user communities should be the ultimate goal of these work efforts; feedback from these communities should be translated back to the scientists to ensure relevant improvements are made from real-world information.

This work is dedicated to the memory of Dr. Eugene H. Wissler (1927–2018). His pioneering efforts modeling heat transfer in the human body provided critical

The authors would also like to thank Dr. Scott Montain for oversight and review

The authors have no conflicts of interest to declare. Funding for this work has been provided by U.S. Army Medical Research and Materiel Command (USAMRMC), Military Operational Medicine Research Program (MOMRP).

ground work that continues to be emulated by researchers.

[121] and the estimated metabolic

*DOI: http://dx.doi.org/10.5772/intechopen.81238*

*5.4.3 Metabolic heat production*

**6. Summary and discussion**

injury risk.

#### *5.4.3 Metabolic heat production*

*Autonomic Nervous System Monitoring - Heart Rate Variability*

Total shivering (TOTMshiv)

Metabolic rate of shivering (Mshiv)

Metabolic rate of shivering (Mshiv)

Metabolic rate to open air (M1)

Total metabolic rate (M2)

Total metabolic rate (M)

Metabolic rate of shivering (Mshiv)

Metabolic rate

*); Wt, weight (lbs).*

**Table 3.**

Maximal shivering (Shivmax)

**Prediction Equation Units References**

kcal h<sup>−</sup><sup>1</sup> [37]

kcal h<sup>−</sup><sup>1</sup> [30]

kcal h<sup>−</sup><sup>1</sup> [117]

W m<sup>−</sup><sup>2</sup> [118]

W m<sup>−</sup><sup>2</sup> [120]

[125]

[126]

W [128]

l O2 min<sup>−</sup><sup>1</sup> [129]

[37]

mLO2 kg<sup>−</sup><sup>1</sup> min<sup>−</sup><sup>1</sup>

<sup>=</sup> <sup>300</sup> <sup>∙</sup> (*Th* <sup>−</sup> *Th*,*set*) <sup>+</sup> 1.35 <sup>∙</sup> (∑*m*=1 <sup>14</sup> *Wa*,*<sup>m</sup>* <sup>∙</sup> (*qs*,*m*̇ <sup>−</sup> *qs*,*set*,*m*) <sup>+</sup> <sup>75</sup> <sup>∙</sup> (∑*m*=1 <sup>14</sup> *Wa*,*<sup>m</sup>* <sup>∙</sup> (*Ts*,*<sup>m</sup>* <sup>−</sup> *Ts*,*set*,*m*)

= 30.5 + 0.348 ∙ *VO*<sup>2</sup>*max* − 0.909 ∙ *BMI* − 0.233 ∙ *age*(*yrs*)

= 60 ∙ (36.6 − *Tty*) ∙ (34.1 − *Ts*)

= 36 ∙ (36.5 − *Tty*) ∙ (32.2 − *Ts*) + 7 ∙ (32.2 − *Ts*)

*dTs*

*dt* <sup>−</sup> 5.01 <sup>∙</sup> (*Ts* <sup>−</sup> 34)

<sup>=</sup> 155.5 <sup>∙</sup> (37 <sup>−</sup> *Tes*) <sup>+</sup> <sup>47</sup> <sup>∙</sup> (33 <sup>−</sup> *Ts*) <sup>−</sup> 1.57 <sup>∙</sup> (33 <sup>−</sup> *Ts*)

*Note: T is temperature; h is head; set is set point of temperatures; Wa,m is a weighting coefficient; qs is heat flux s is skin; BMI is body mass index; ty is Tympanic membrane; re is rectal; and es is esophageal; BF% is body fat percentage.*

**Prediction Equation Units References**

) 2 + *η*(*M* + *L*)

–3.94∙*S* + 9.66)

*Note: G is grade (° for Ref. [125], % for others); Ht, height (inches for Ref. [129]); L, external load (kg); M, mass* 

+ 0.35∙*S*∙*G*)

\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ √ \_\_\_\_\_ *BF*%

<sup>=</sup> *<sup>M</sup>*<sup>1</sup> <sup>+</sup> (894.15 <sup>−</sup> 23.79 <sup>∙</sup> *Tre*) W m<sup>−</sup><sup>2</sup> [118]

<sup>=</sup> 0.0314 <sup>∙</sup> (*Ts* <sup>−</sup> 42.4) <sup>∙</sup> (*Tre* <sup>−</sup> 41.4) W kg<sup>−</sup><sup>1</sup> [119]

=1.44 + 1.94∙*S*0.43 + 0.24∙*S*<sup>4</sup> W kg<sup>−</sup><sup>1</sup> [124]

kg<sup>−</sup><sup>1</sup> min<sup>−</sup><sup>1</sup>

kg<sup>−</sup><sup>1</sup> min<sup>−</sup><sup>1</sup>

 *for others); VO2-rest, resting oxygen consumption (ml kg<sup>−</sup><sup>1</sup>*

=3.5 + 6∙*S* + 1.08∙*S*∙*G* mLO2

=17.7–18.138∙*S* + 9.72∙*S*<sup>2</sup> mLO2

∙(1.92∙*S*0.176–1.445)

=1.4 + 0.42∙*G* + 3.68∙*S* − 0.01∙M − 0.03∙Age W kg<sup>−</sup><sup>1</sup> [127]

2

= 41.31 − 57.77 ∙ \_\_\_

*Methods for predicting shivering related model calculations.*

cold exposure the shivering response is a critical element to model, as the production of heat protects the body core temperature despite skin to the ambient heat loss. **Table 3** outlines some of the modeling approaches that have been used to predict the shivering response as they relate to the total metabolic rate (*M*) and the

=1.5∙*M* + 2∙(*M* + *L*)∙(*L*∙*M*<sup>−</sup><sup>1</sup>

=*Ht*∙(0.0136∙*Ht* − 0.375)<sup>−</sup><sup>1</sup>

∙*Wt*∙105

(1.5∙*S*<sup>2</sup>

∙(0.82∙*S*<sup>2</sup>

**58**

*min<sup>−</sup><sup>1</sup>*

**Table 4.**

heat production from shivering (*Mshiv*).

*(kg); η, terrain factor; S, speed (mph for Ref. [129], m s<sup>−</sup><sup>1</sup>*

*Methods for predicting metabolic rates during walking or standing.*

An individual's metabolic heat production can be estimated at rest and during activity using the assumed basal rate of 58.2 W/m2 [121] and the estimated metabolic equivalents (METS) of activity; where 1 MET is resting. Ainsworth et al. [122] outlines a wide range of activities and their associated MET level for reference. However, there are metabolic rate estimation methods available based on energy costs of standing or walking (**Table 4**). Recently work has also been published that makes corrections to some of these prediction methods specific to traveling over snow terrain [123].

#### **6. Summary and discussion**

Mathematical models and decision aids are tools for inspiring advancements within the field of thermophysiology, and for providing solutions to help mitigate injury risk.

Scientifically based models have been used in the development of public [97, 98, 103, 104, 130–132] and military guidance [75, 131, 133], for forensic assessments [134–140], as well in the creation of operational tools for survival [141, 142]. Notably, the use of Xu and Werner's six cylinder model [41] was used to develop the Probability of Survival Decision Aid (PSDA), a computer model used to predict hypothermia and dehydration impact on functional time (i.e., duration of ability for useful work), and survival time while exposed to marine environments [67, 143, 144]. The PSDA model is underpinned by the rational principles described herein and the outputs are provided in a customized graphical user interface. This tool has been transitioned for use by Search and Rescue (SaR) personnel and continues to be refined and verified based on real-world feedback and data collected [144].

There is a need for continued advancement in the development of individualized modeling methods such as finite element models as well as providing models and decision aids that can be used in dynamic settings and for complex scenarios with prolonged durations. Additionally, inclusion of probabilistic and statistically based risk factors should be used as elements that help improve individualized predictions. The accessibility of the information from these tools continues to be a challenge for the scientific community. While providing usable information to the public, military, and other user communities should be the ultimate goal of these work efforts; feedback from these communities should be translated back to the scientists to ensure relevant improvements are made from real-world information.

#### **Acknowledgements**

This work is dedicated to the memory of Dr. Eugene H. Wissler (1927–2018). His pioneering efforts modeling heat transfer in the human body provided critical ground work that continues to be emulated by researchers.

The authors would also like to thank Dr. Scott Montain for oversight and review of this chapter.

#### **Conflict of interest**

The authors have no conflicts of interest to declare. Funding for this work has been provided by U.S. Army Medical Research and Materiel Command (USAMRMC), Military Operational Medicine Research Program (MOMRP).

### **Disclaimer**

The views expressed in this paper are those of the authors and do not reflect the official policy of the Department of Army, Department of Defense, or the US Government.

#### **Author details**

Adam W. Potter1,2\*, David P. Looney1 , Xiaojiang Xu1 , William R. Santee1,3 and Shankar Srinivasan<sup>2</sup>

1 Biophysics and Biomedical Modeling Division, United States Army Research Institute of Environmental Medicine, Natick, Massachusetts, United States of America

2 Rutgers University, School of Biomedical and Health Sciences, Newark, NJ, United States of America

3 Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, United States of America

\*Address all correspondence to: adam.w.potter.civ@mail.mil

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**61**

*Modeling Thermoregulatory Responses to Cold Environments*

[11] Potter AW, Blanchard LA, Friedl KE, Cadarette BS, Hoyt RW. Mathematical prediction of core body temperature from environment, activity, and clothing: The heat strain decision aid (HSDA). Journal of Thermal Biology.

[12] Fanger PO. Thermal comfort. Analysis and applications in

[13] Gagge AP, Stolwijk JA, Saltin B. Comfort and thermal sensations and associated physiological responses during exercise at various ambient temperatures. Environmental Research.

environmental engineering. In: Thermal Comfort: Analysis and Applications in Environmental Engineering. Copenhaen, Denmark: Danish Technical Press; 1970

[14] Gagge AP. An effective temperature scale based on a simple model of human physiological regulatory response. ASHRAE Transactions. 1971;**77**:247-262

[15] Nishi Y, Gagge AP. Humid operative temperature. A biophysical index of thermal sensation and discomfort. Journal de Physiologie. 1971;**63**(3):365

[16] Takada S, Kobayashi H, Matsushita T. Thermal model of human body fitted with individual characteristics of body temperature regulation. Building and Environment. 2009;**44**(3):463-470

[17] Azer NZ, Hsu S. The prediction of thermal sensation from a simple model of human physiological regulatory response. ASHRAE Transactions.

[18] Jones BW, Ogawa Y. Transient response of the human-clothing system. Journal of Thermal Biology.

[19] Kingma BR, Frijns AJ, Schellen L, van Marken Lichtenbelt WD. Beyond

1977;**83**(Pt 1):88-102

1993;**18**(5-6):413-416

2017;**64**:78-85

1969;**2**(3):209-229

*DOI: http://dx.doi.org/10.5772/intechopen.81238*

[1] Carter IIIR, Cheuvront SN, Williams JO, Kolka MA, Stephenson LA, Sawka MN, et al. Epidemiology of hospitalizations and deaths from heat illness in soldiers. Medicine & Science in Sports & Exercise. 2005;**37**(8):1338-1344

**References**

[2] DeGroot DW, Castellani JW,

[3] Blagden C. Experiments and observations in an heated room. Philosophical Transactions.

[4] Fourier J. Theorie analytique de la chaleur, par M. Fourier. Paris, France: Chez Firmin Didot, père et fils; p. 1822

[5] Pennes HH. Analysis of tissue and arterial blood temperatures in the resting human forearm. Journal of Applied Physiology. 1948;**1**(2):93-122

[6] Lefevre J. Chaleur animale et

[7] Burton AC. The application of the theory of heat flow to the study of energy metabolism: Five figures. The Journal of Nutrition.

bioénergétique. Paris, France: Masson et

[8] Fu G. A transient, 3-D mathematical thermal model for the clothed human [Ph.D. dissertation]. Kansas State University, Manhattan, Kansas; 1995

[9] Givoni B, Goldman RF. Predicting metabolic energy cost. Journal of Applied Physiology. 1971;**30**(3):429-433

[10] Givoni B, Goldman RF. Predicting rectal temperature response to work, environment, and clothing. Journal of Applied Physiology. 1972;**32**(6):812-822

2003;**74**(5):564-570

1775;**65**:111-123

cie; 1911

1934;**7**(5):497-533

Williams JO, Amoroso PJ. Epidemiology of US Army cold weather injuries, 1980-1999. Aviation, Space, and Environmental Medicine.

### **References**

*Autonomic Nervous System Monitoring - Heart Rate Variability*

The views expressed in this paper are those of the authors and do not reflect the official policy of the Department of Army, Department of Defense, or the US

**Disclaimer**

Government.

**Author details**

America

and Shankar Srinivasan<sup>2</sup>

United States of America

States of America

Adam W. Potter1,2\*, David P. Looney1

**60**

provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

, Xiaojiang Xu1

1 Biophysics and Biomedical Modeling Division, United States Army Research Institute of Environmental Medicine, Natick, Massachusetts, United States of

2 Rutgers University, School of Biomedical and Health Sciences, Newark, NJ,

\*Address all correspondence to: adam.w.potter.civ@mail.mil

3 Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, United

, William R. Santee1,3

[1] Carter IIIR, Cheuvront SN, Williams JO, Kolka MA, Stephenson LA, Sawka MN, et al. Epidemiology of hospitalizations and deaths from heat illness in soldiers. Medicine & Science in Sports & Exercise. 2005;**37**(8):1338-1344

[2] DeGroot DW, Castellani JW, Williams JO, Amoroso PJ. Epidemiology of US Army cold weather injuries, 1980-1999. Aviation, Space, and Environmental Medicine. 2003;**74**(5):564-570

[3] Blagden C. Experiments and observations in an heated room. Philosophical Transactions. 1775;**65**:111-123

[4] Fourier J. Theorie analytique de la chaleur, par M. Fourier. Paris, France: Chez Firmin Didot, père et fils; p. 1822

[5] Pennes HH. Analysis of tissue and arterial blood temperatures in the resting human forearm. Journal of Applied Physiology. 1948;**1**(2):93-122

[6] Lefevre J. Chaleur animale et bioénergétique. Paris, France: Masson et cie; 1911

[7] Burton AC. The application of the theory of heat flow to the study of energy metabolism: Five figures. The Journal of Nutrition. 1934;**7**(5):497-533

[8] Fu G. A transient, 3-D mathematical thermal model for the clothed human [Ph.D. dissertation]. Kansas State University, Manhattan, Kansas; 1995

[9] Givoni B, Goldman RF. Predicting metabolic energy cost. Journal of Applied Physiology. 1971;**30**(3):429-433

[10] Givoni B, Goldman RF. Predicting rectal temperature response to work, environment, and clothing. Journal of Applied Physiology. 1972;**32**(6):812-822 [11] Potter AW, Blanchard LA, Friedl KE, Cadarette BS, Hoyt RW. Mathematical prediction of core body temperature from environment, activity, and clothing: The heat strain decision aid (HSDA). Journal of Thermal Biology. 2017;**64**:78-85

[12] Fanger PO. Thermal comfort. Analysis and applications in environmental engineering. In: Thermal Comfort: Analysis and Applications in Environmental Engineering. Copenhaen, Denmark: Danish Technical Press; 1970

[13] Gagge AP, Stolwijk JA, Saltin B. Comfort and thermal sensations and associated physiological responses during exercise at various ambient temperatures. Environmental Research. 1969;**2**(3):209-229

[14] Gagge AP. An effective temperature scale based on a simple model of human physiological regulatory response. ASHRAE Transactions. 1971;**77**:247-262

[15] Nishi Y, Gagge AP. Humid operative temperature. A biophysical index of thermal sensation and discomfort. Journal de Physiologie. 1971;**63**(3):365

[16] Takada S, Kobayashi H, Matsushita T. Thermal model of human body fitted with individual characteristics of body temperature regulation. Building and Environment. 2009;**44**(3):463-470

[17] Azer NZ, Hsu S. The prediction of thermal sensation from a simple model of human physiological regulatory response. ASHRAE Transactions. 1977;**83**(Pt 1):88-102

[18] Jones BW, Ogawa Y. Transient response of the human-clothing system. Journal of Thermal Biology. 1993;**18**(5-6):413-416

[19] Kingma BR, Frijns AJ, Schellen L, van Marken Lichtenbelt WD. Beyond the classic thermoneutral zone: Including thermal comfort. Temperature. 2014;**1**(2):142-149

[20] Kohri I, Mochida T. Evaluation method of thermal comfort in a vehicle with a dispersed two-node model part 1—Development of dispersed two-node model. Journal of the Human-Environment System. 2002;**6**(1):19-29

[21] Kaynakli O, Unver U, Kilic M. Evaluating thermal environments for sitting and standing posture. International Communications in Heat and Mass Transfer. 2003;**30**(8):1179-1188

[22] Kaynakli O, Kilic M. Investigation of indoor thermal comfort under transient conditions. Building and Environment. 2005;**40**(2):165-174

[23] Foda E, Sirén K. A new approach using the Pierce two-node model for different body parts. International Journal of Biometeorology. 2011;**55**(4):519-532

[24] Crosbie RJ, Hardy JD, Fessenden E. Electrical analog simulation of temperature regulation in man. IRE Transactions on Bio-Medical Electronics. 1961;**8**(4):245-252

[25] Fiala D, Lomas KJ, Stohrer M. A computer model of human thermoregulation for a wide range of environmental conditions: The passive system. Journal of Applied Physiology. 1999;**87**(5):1957-1972

[26] Fiala D, Lomas KJ, Stohrer M. Computer prediction of human thermoregulatory and temperature responses to a wide range of environmental conditions. International Journal of Biometeorology. 2001;**45**(3):143-159

[27] Kingma BR. Human thermoregulation; a synergy between physiology and mathematical modeling [doctoral dissertation]. Maastricht University

[28] Kingma BR, Frijns AJ, Saris WH, van Steenhoven AA, van Marken Lichtenbelt WD. Mathematical modeling of human thermoregulation: A neurophysiological approach to vasoconstriction. In: Computational Intelligence. Berlin, Heidelberg: Springer; 2012. pp. 307-316

[29] Davoodi F, Hasanzadeh H, Zolfaghari SA, Maerefat M. Developing a new individualized 3-node model for evaluating the effects of personal factors on thermal sensation. Journal of Thermal Biology. 2017;**69**:1-2

[30] Stolwijk JAJ, Hardy JD. Temperature regulation in man—A theoretical study. Pflügers Archiv für die Gesamte Physiologie des Menschen und der Tiere. 1966;**291**:129-162

[31] Stolwijk JAJ. A Mathematical Model of Physiological Temperature Regulation in Man. NASA-CR-1855. Washington, DC: National Aeronaucis and Space Administration; 1971

[32] Stolwijk JAJ. Mathematical models of thermal regulation. Annals of the New York Academy of Sciences. 1980;**335**(1):98-106

[33] Stolwijk JAJ, Hardy JD. "Control of Body Temperature". Comprehensive Physiology 2011, Supplement 26: Handbook of Physiology, Reactions to Environmental Agents. First Published in Print 1977. John Wiley & Sons, Inc.; 2010. pp. 45-68. DOI: 10.1002/cphy.cp090104

[34] Montgomery LD. A model of heat transfer in immersed man. Annals of Biomedical Engineering. 1974;**2**(1):19-46

[35] Montgomery LD. Biothermal simulation of scuba divers. Aviation, Space, and Environmental Medicine. 1975;**46**(6):814-818

**63**

*Modeling Thermoregulatory Responses to Cold Environments*

[44] Wissler EH. A mathematical model of the human thermal system. The Bulletin of Mathematical Biophysics.

[45] Wissler EH. In: Shitzer A, Eberhart R, editors. Mathematical Simulation of Human Thermal Behavior Using Whole Body Models. New York: Plenum Press, Heat Transfer in Medicine and Biology;

[46] Smith CE. A transient 3-D model of the human thermal system [doctoral dissertation, PhD Thesis]. Kansas State

[47] Ferreira MS, Yanagihara JI. A transient three-dimensional heat transfer model of the human body. International Communications in Heat and Mass Transfer. 2009;**36**(7):718-724

[48] Schwarz M, Krueger MW, Busch HJ, Benk C, Heilmann C. Model-based assessment of tissue perfusion and temperature in deep hypothermic patients. IEEE Transactions on Biomedical Engineering. 2010;**57**(7):1577-1586

[49] Sun X, Eckels S, Zheng ZC. An improved thermal model of the human body. HVAC&R Research.

C. Assessment of comfortable clothing thermal resistance using a multi-scale human thermoregulatory model. International Journal of Heat and Mass

[51] Molnar GW. Heat transfer through

2012;**18**(3):323-338

[50] Tang Y, He Y, Shao H, Ji

Transfer. 2016;**98**:568-583

1957:15-45

the hand. In: Fisher FR, editor. Protection and Functioning of the Hands in Cold Climates. Washington, DC: National Academy of Sciences;

[52] Shitzer AV, Stroschein LA, Santee WR, Gonzalez RR, Pandolf KB. Quantification of conservative

1964;**26**:147-166

1985. pp. 325-373

University; 1991

*DOI: http://dx.doi.org/10.5772/intechopen.81238*

[37] Gordon RG, Roemer RB, Horvath SM. A mathematical model of the human temperature regulatory system-transient cold exposure response. IEEE Transactions on Biomedical Engineering.

[38] Tikuisis PE, Gonzalez RR, Pandolf KB. Thermoregulatory model for immersion of humans in cold water. Journal of Applied Physiology.

[36] Kuznetz LH. Control of thermal balance by a liquid circulating garment based on a mathematical representation of the human thermoregulatory system [Ph.D. thesis]. Berkeley: California

Univ.; 1976

1976;**6**:434-444

1988;**64**(2):719-727

1988;**59**(8):742-748

1993;**12**:123-134

1997;**16**(2):61-75

2009;**44**(9):1777-1787

1961;**16**:734-740

[43] Wissler EH. Steady-state temperature distribution in man. Journal of Applied Physiology.

[39] Tikuisis PE, Gonzalez RR, Pandolf KB. Prediction of human thermoregulatory responses and endurance time in water at 20 and 24 degrees C. Aviation, Space, and Environmental Medicine.

[40] Werner J, Webb P. A six-cylinder model of human thermoregulation for general use on personal computers. The Annals of Physiological Anthropology.

[41] Xu X, Werner J. A dynamic model of the human/clothing/environmentsystem. Applied Human Science: Journal of Physiological Anthropology.

[42] Munir A, Takada S, Matsushita T. Re-evaluation of Stolwijk's 25-node human thermal model under thermaltransient conditions: Prediction of skin temperature in low-activity conditions. Building and Environment. *Modeling Thermoregulatory Responses to Cold Environments DOI: http://dx.doi.org/10.5772/intechopen.81238*

[36] Kuznetz LH. Control of thermal balance by a liquid circulating garment based on a mathematical representation of the human thermoregulatory system [Ph.D. thesis]. Berkeley: California Univ.; 1976

[37] Gordon RG, Roemer RB, Horvath SM. A mathematical model of the human temperature regulatory system-transient cold exposure response. IEEE Transactions on Biomedical Engineering. 1976;**6**:434-444

[38] Tikuisis PE, Gonzalez RR, Pandolf KB. Thermoregulatory model for immersion of humans in cold water. Journal of Applied Physiology. 1988;**64**(2):719-727

[39] Tikuisis PE, Gonzalez RR, Pandolf KB. Prediction of human thermoregulatory responses and endurance time in water at 20 and 24 degrees C. Aviation, Space, and Environmental Medicine. 1988;**59**(8):742-748

[40] Werner J, Webb P. A six-cylinder model of human thermoregulation for general use on personal computers. The Annals of Physiological Anthropology. 1993;**12**:123-134

[41] Xu X, Werner J. A dynamic model of the human/clothing/environmentsystem. Applied Human Science: Journal of Physiological Anthropology. 1997;**16**(2):61-75

[42] Munir A, Takada S, Matsushita T. Re-evaluation of Stolwijk's 25-node human thermal model under thermaltransient conditions: Prediction of skin temperature in low-activity conditions. Building and Environment. 2009;**44**(9):1777-1787

[43] Wissler EH. Steady-state temperature distribution in man. Journal of Applied Physiology. 1961;**16**:734-740

[44] Wissler EH. A mathematical model of the human thermal system. The Bulletin of Mathematical Biophysics. 1964;**26**:147-166

[45] Wissler EH. In: Shitzer A, Eberhart R, editors. Mathematical Simulation of Human Thermal Behavior Using Whole Body Models. New York: Plenum Press, Heat Transfer in Medicine and Biology; 1985. pp. 325-373

[46] Smith CE. A transient 3-D model of the human thermal system [doctoral dissertation, PhD Thesis]. Kansas State University; 1991

[47] Ferreira MS, Yanagihara JI. A transient three-dimensional heat transfer model of the human body. International Communications in Heat and Mass Transfer. 2009;**36**(7):718-724

[48] Schwarz M, Krueger MW, Busch HJ, Benk C, Heilmann C. Model-based assessment of tissue perfusion and temperature in deep hypothermic patients. IEEE Transactions on Biomedical Engineering. 2010;**57**(7):1577-1586

[49] Sun X, Eckels S, Zheng ZC. An improved thermal model of the human body. HVAC&R Research. 2012;**18**(3):323-338

[50] Tang Y, He Y, Shao H, Ji C. Assessment of comfortable clothing thermal resistance using a multi-scale human thermoregulatory model. International Journal of Heat and Mass Transfer. 2016;**98**:568-583

[51] Molnar GW. Heat transfer through the hand. In: Fisher FR, editor. Protection and Functioning of the Hands in Cold Climates. Washington, DC: National Academy of Sciences; 1957:15-45

[52] Shitzer AV, Stroschein LA, Santee WR, Gonzalez RR, Pandolf KB. Quantification of conservative

**62**

*Autonomic Nervous System Monitoring - Heart Rate Variability*

physiology and mathematical modeling [doctoral dissertation]. Maastricht

[28] Kingma BR, Frijns AJ, Saris WH, van Steenhoven AA, van Marken Lichtenbelt WD. Mathematical

modeling of human thermoregulation: A neurophysiological approach to vasoconstriction. In: Computational Intelligence. Berlin, Heidelberg: Springer; 2012. pp. 307-316

Zolfaghari SA, Maerefat M. Developing a new individualized 3-node model for evaluating the effects of personal factors on thermal sensation. Journal of

[30] Stolwijk JAJ, Hardy JD. Temperature regulation in man—A theoretical study. Pflügers Archiv für die Gesamte Physiologie des Menschen und der

[29] Davoodi F, Hasanzadeh H,

Thermal Biology. 2017;**69**:1-2

Tiere. 1966;**291**:129-162

1980;**335**(1):98-106

[31] Stolwijk JAJ. A Mathematical Model of Physiological Temperature Regulation in Man. NASA-CR-1855. Washington, DC: National Aeronaucis and Space Administration; 1971

[32] Stolwijk JAJ. Mathematical models of thermal regulation. Annals of the New York Academy of Sciences.

[33] Stolwijk JAJ, Hardy JD. "Control of Body Temperature". Comprehensive Physiology 2011, Supplement 26: Handbook of Physiology, Reactions to Environmental Agents. First Published in Print 1977. John Wiley & Sons, Inc.; 2010. pp. 45-68. DOI: 10.1002/cphy.cp090104

[34] Montgomery LD. A model of heat transfer in immersed man. Annals of Biomedical Engineering. 1974;**2**(1):19-46

[35] Montgomery LD. Biothermal simulation of scuba divers. Aviation, Space, and Environmental Medicine.

1975;**46**(6):814-818

University

the classic thermoneutral zone: Including thermal comfort. Temperature. 2014;**1**(2):142-149

[21] Kaynakli O, Unver U, Kilic M. Evaluating thermal environments for sitting and standing posture. International Communications in Heat and Mass Transfer. 2003;**30**(8):1179-1188

[22] Kaynakli O, Kilic M. Investigation of indoor thermal comfort under transient conditions. Building and Environment.

[23] Foda E, Sirén K. A new approach using the Pierce two-node model for different body parts. International Journal of Biometeorology.

[24] Crosbie RJ, Hardy JD, Fessenden E. Electrical analog simulation of temperature regulation in man. IRE Transactions on Bio-Medical Electronics. 1961;**8**(4):245-252

[25] Fiala D, Lomas KJ, Stohrer M. A computer model of human thermoregulation for a wide range of environmental conditions: The passive system. Journal of Applied Physiology.

[26] Fiala D, Lomas KJ, Stohrer M. Computer prediction of human thermoregulatory and temperature responses to a wide range of

Journal of Biometeorology.

[27] Kingma BR. Human

2001;**45**(3):143-159

environmental conditions. International

thermoregulation; a synergy between

1999;**87**(5):1957-1972

2002;**6**(1):19-29

2005;**40**(2):165-174

2011;**55**(4):519-532

[20] Kohri I, Mochida T. Evaluation method of thermal comfort in a vehicle with a dispersed two-node model part 1—Development of dispersed two-node model. Journal of the Human-Environment System. endurance times in thermally insulated cold-stressed digits. Journal of Applied Physiology. 1991;**71**(6):2528-2535

[53] Shitzer AV, Stroschein LA, Gonzalez RR, Pandolf KB. Lumped-parameter tissue temperature-blood perfusion model of a cold-stressed fingertip. Journal of Applied Physiology. 1996;**80**(5):1829-1834

[54] Shitzer A, Stroschein LA, Vital P, Gonzalez RR, Pandolf KB. Numerical analysis of an extremity in a cold environment including countercurrent arterio-venous heat exchange. Journal of Biomechanical Engineering. 1997;**119**(2):179-186

[55] Tikuisis P, Ducharme MB. Finiteelement solution of thermal conductivity of muscle during cold water immersion. Journal of Applied Physiology. 1991;**70**(6):2673-2681

[56] Ducharme MB, Tikuisis P. Forearm temperature profile during the transient phase of thermal stress. European Journal of Applied Physiology and Occupational Physiology. 1992;**64**(5):395-401

[57] Tikuisis P. Finger cooling during cold air exposure. Bulletin of the American Meteorological Society. 2004;**85**(5):717-724

[58] Montgomery LD, Williams BA. Effect of ambient temperature on the thermal profile of the human forearm, hand, and fingers. Annals of Biomedical Engineering. 1976;**4**(3):209-219

[59] Lotens WA. Simulation of hand cooling due to touching cold materials. European Journal of Applied Physiology and Occupational Physiology. 1992;**65**(1):59-65

[60] Lotens WA, Heus R, Van de Linde FJG. A 2-node thermoregulatory model for the foot. In: Mercer JB editor. Thermal physiology. Elsevier Science Publishers; 1989:769-775

[61] Xu X, Endrusick TL, Santee WB, Kolka MA. Simulation of toe thermal responses to cold exposure while wearing protective footwear. SAE Technical Paper. 2005

[62] Tikuisis P, Ducharme MB, Brajkovic D. Prediction of facial cooling while walking in cold wind. Computers in Biology and Medicine. 2007;**37**(9):1225-1231

[63] Tikuisis P, Osczevski RJ. Dynamic model of facial cooling. Journal of Applied Meteorology. 2002;**41**(12):1241-1246

[64] Tikuisis P. Predicting survival time for cold exposure. International Journal of Biometeorology. 1995;**39**(2):94-102

[65] Tikuisis P. Prediction of survival time at sea based on observed body cooling rates. Aviation, Space, and Environmental Medicine. 1997;**68**(5):441-448

[66] Xu X, Tikuisis P, Gonzalez R, Giesbrecht G. Thermoregulatory model for prediction of long-term cold exposure. Computers in Biology and Medicine. 2005;**35**(4):287-298

[67] Xu X, Turner CA, Santee WR. Survival time prediction in marine environments. Journal of Thermal Biology. 2011;**36**(6):340-345

[68] Xu X, Tikuisis P, Giesbrecht G. A mathematical model for human brain cooling during cold-water near-drowning. Journal of Applied Physiology. 1999;**86**(1):265-272

[69] Castellani JW, Young AJ, Ducharme MB, Giesbrecht GG, Glickman E, Sallis RE. Prevention of cold injuries during exercise. Medicine & Science in Sports & Exercise. 2006;**38**:2012-2029

[70] Keatinge WR, Cannon P. Freezingpoint of human skin. Lancet. 1960;**I**:11-14

**65**

*Modeling Thermoregulatory Responses to Cold Environments*

in man. Journal of Applied Physiology.

[79] Charkoudian N. Skin blood flow in adult human thermoregulation: How it works, when it does not, and why. Mayo Clinic Proceedings. 2003;**78**(5):603-612

[80] Astrand A, Rodahl I. Textbook of Work Physiology. New York, NY: McGraw Hill; 1986. pp. 104-112

[81] Potter AW, Gonzalez JA, Karis AJ, Xu X. Biophysical assessment and predicted thermophysiologic effects of body armor. PLoS One.

[82] Potter AW, Karis AJ, Gonzalez JA. Biophysical characterization and predicted human thermal responses to US army body armor protection levels (BAPL). In: Technical Report, T13-5, ADA#585406. Natick, MA 01760 USA: U.S. Army Research Institute of Environmental Medicine ; 2013. Available from: www.dtic.mil/dtic/tr/

[83] Larsen B, Netto K, Aisbett B. The effect of body armor on performance, thermal stress, and exertion: A critical review. Military Medicine.

[84] Xu X, Gonzalez JA, Karis AJ, Rioux TP, Potter AW. Use of thermal mannequins for evaluation of heat stress imposed by personal protective equipment. In: Shiels B, Lehtonen K, editors. Performance of Protective Clothing and Equipment: 10th Volume, Risk Reduction through Research and Testing, ASTM STP1593. West Conshohocken, PA: ASTM International; 2016. pp. 286-296

[85] Potter AW, Gonzalez JA, Karis AJ, Santee WR, Rioux TP, Blanchard LA. Biophysical characteristics and measured wind effects of chemical protective ensembles with and without body armor. In: Technical Report,

2015;**10**(7):e0132698

fulltext/u2/a585406.pdf

2011;**176**(11):1265-1273

1973;**35**:798-803

*DOI: http://dx.doi.org/10.5772/intechopen.81238*

[71] Hamlet MP. Nonfreezing cold injuries. In: Auebach PS, editor. Textbook of Wilderness Medicine. St. Louis, MO: Mosby; 2001. pp. 129-134

[72] Evans TM, Rundell KW, Beck KC, Levine AM, Baumann JM. Cold air inhalation does not affect the severity of EIB after exercise or eucapnic voluntary hyperventilation. Medicine & Science in Sports & Exercise. 2005;**37**(4):544-549

[73] Wilber RL, Rundell KW, Szmedra

L, Jenkinson DM, Im J, Drake SD. Incidence of exercise-induced bronchospasm in Olympic winter sport athletes. Medicine & Science in Sports & Exercise. 2000;**32**(4):732-737

[74] Pozos RS, Danzl DF. Human physiological responses to cold stress and hypothermia. In: Pandolf KB, Burr RE, editors. Textbooks of Military Medicine: Medical Aspects of Harsh Environments. Vol. 1. Falls Church, YA: Office of the Surgeon General, U. S.

Army; 2002. pp. 351-382

2001;**33**(3):422-430

[75] Department of the Army.

Prevention and Management of Cold-Weather Injuries. Washington, DC: 2005. Report No.: TB MED 508

[76] Sawka MN, Latzka WA, Montain SJ, Cadarette BS, Kolka MA, Kraning KK, et al. Physiologic tolerance to uncompensable heat: Intermittent exercise, field vs laboratory. Medicine and Science in Sports and Exercise.

[77] Sawka MN, Young AJ. Physiological

systems and their responses to conditions of heat and cold. In: American College of Sports Medicine. ACSM's Advanced Exercise Physiology. Philadelphia, PA: Lippincott Williams &

Wilkins; 2006. pp. 535-563

[78] Johnson JM, Niederberger MA, Rowell LB, Eisman MM, Brengelmann GL. Competition between cutaneous vasodilator and vasoconstrictor reflexes

#### *Modeling Thermoregulatory Responses to Cold Environments DOI: http://dx.doi.org/10.5772/intechopen.81238*

[71] Hamlet MP. Nonfreezing cold injuries. In: Auebach PS, editor. Textbook of Wilderness Medicine. St. Louis, MO: Mosby; 2001. pp. 129-134

*Autonomic Nervous System Monitoring - Heart Rate Variability*

[61] Xu X, Endrusick TL, Santee WB, Kolka MA. Simulation of toe thermal responses to cold exposure while wearing protective footwear. SAE

Technical Paper. 2005

2007;**37**(9):1225-1231

[63] Tikuisis P, Osczevski

2002;**41**(12):1241-1246

1997;**68**(5):441-448

RJ. Dynamic model of facial cooling. Journal of Applied Meteorology.

[64] Tikuisis P. Predicting survival time for cold exposure. International Journal of Biometeorology. 1995;**39**(2):94-102

[65] Tikuisis P. Prediction of survival time at sea based on observed body cooling rates. Aviation, Space, and Environmental Medicine.

[66] Xu X, Tikuisis P, Gonzalez R, Giesbrecht G. Thermoregulatory model for prediction of long-term cold exposure. Computers in Biology and Medicine. 2005;**35**(4):287-298

[67] Xu X, Turner CA, Santee

[68] Xu X, Tikuisis P, Giesbrecht G. A mathematical model for human brain cooling during cold-water near-drowning. Journal of Applied Physiology. 1999;**86**(1):265-272

& Exercise. 2006;**38**:2012-2029

point of human skin. Lancet.

1960;**I**:11-14

WR. Survival time prediction in marine environments. Journal of Thermal Biology. 2011;**36**(6):340-345

[69] Castellani JW, Young AJ, Ducharme MB, Giesbrecht GG, Glickman E, Sallis RE. Prevention of cold injuries during exercise. Medicine & Science in Sports

[70] Keatinge WR, Cannon P. Freezing-

[62] Tikuisis P, Ducharme MB, Brajkovic D. Prediction of facial cooling while walking in cold wind. Computers in Biology and Medicine.

endurance times in thermally insulated cold-stressed digits. Journal of Applied Physiology. 1991;**71**(6):2528-2535

[53] Shitzer AV, Stroschein LA, Gonzalez RR, Pandolf KB. Lumped-parameter tissue temperature-blood perfusion model of a cold-stressed fingertip. Journal of Applied Physiology.

[54] Shitzer A, Stroschein LA, Vital P, Gonzalez RR, Pandolf KB. Numerical analysis of an extremity in a cold environment including countercurrent arterio-venous heat exchange. Journal of Biomechanical Engineering.

[55] Tikuisis P, Ducharme MB. Finite-

[56] Ducharme MB, Tikuisis P. Forearm temperature profile during the transient phase of thermal stress. European Journal of Applied Physiology and Occupational

[57] Tikuisis P. Finger cooling during cold air exposure. Bulletin of the American Meteorological Society.

BA. Effect of ambient temperature on the thermal profile of the human forearm, hand, and fingers. Annals of Biomedical

Physiology. 1992;**64**(5):395-401

[58] Montgomery LD, Williams

Engineering. 1976;**4**(3):209-219

and Occupational Physiology.

Publishers; 1989:769-775

1992;**65**(1):59-65

[59] Lotens WA. Simulation of hand cooling due to touching cold materials. European Journal of Applied Physiology

[60] Lotens WA, Heus R, Van de Linde FJG. A 2-node thermoregulatory model for the foot. In: Mercer JB editor. Thermal physiology. Elsevier Science

2004;**85**(5):717-724

element solution of thermal conductivity of muscle during cold water immersion. Journal of Applied Physiology. 1991;**70**(6):2673-2681

1996;**80**(5):1829-1834

1997;**119**(2):179-186

**64**

[72] Evans TM, Rundell KW, Beck KC, Levine AM, Baumann JM. Cold air inhalation does not affect the severity of EIB after exercise or eucapnic voluntary hyperventilation. Medicine & Science in Sports & Exercise. 2005;**37**(4):544-549

[73] Wilber RL, Rundell KW, Szmedra L, Jenkinson DM, Im J, Drake SD. Incidence of exercise-induced bronchospasm in Olympic winter sport athletes. Medicine & Science in Sports & Exercise. 2000;**32**(4):732-737

[74] Pozos RS, Danzl DF. Human physiological responses to cold stress and hypothermia. In: Pandolf KB, Burr RE, editors. Textbooks of Military Medicine: Medical Aspects of Harsh Environments. Vol. 1. Falls Church, YA: Office of the Surgeon General, U. S. Army; 2002. pp. 351-382

[75] Department of the Army. Prevention and Management of Cold-Weather Injuries. Washington, DC: 2005. Report No.: TB MED 508

[76] Sawka MN, Latzka WA, Montain SJ, Cadarette BS, Kolka MA, Kraning KK, et al. Physiologic tolerance to uncompensable heat: Intermittent exercise, field vs laboratory. Medicine and Science in Sports and Exercise. 2001;**33**(3):422-430

[77] Sawka MN, Young AJ. Physiological systems and their responses to conditions of heat and cold. In: American College of Sports Medicine. ACSM's Advanced Exercise Physiology. Philadelphia, PA: Lippincott Williams & Wilkins; 2006. pp. 535-563

[78] Johnson JM, Niederberger MA, Rowell LB, Eisman MM, Brengelmann GL. Competition between cutaneous vasodilator and vasoconstrictor reflexes in man. Journal of Applied Physiology. 1973;**35**:798-803

[79] Charkoudian N. Skin blood flow in adult human thermoregulation: How it works, when it does not, and why. Mayo Clinic Proceedings. 2003;**78**(5):603-612

[80] Astrand A, Rodahl I. Textbook of Work Physiology. New York, NY: McGraw Hill; 1986. pp. 104-112

[81] Potter AW, Gonzalez JA, Karis AJ, Xu X. Biophysical assessment and predicted thermophysiologic effects of body armor. PLoS One. 2015;**10**(7):e0132698

[82] Potter AW, Karis AJ, Gonzalez JA. Biophysical characterization and predicted human thermal responses to US army body armor protection levels (BAPL). In: Technical Report, T13-5, ADA#585406. Natick, MA 01760 USA: U.S. Army Research Institute of Environmental Medicine ; 2013. Available from: www.dtic.mil/dtic/tr/ fulltext/u2/a585406.pdf

[83] Larsen B, Netto K, Aisbett B. The effect of body armor on performance, thermal stress, and exertion: A critical review. Military Medicine. 2011;**176**(11):1265-1273

[84] Xu X, Gonzalez JA, Karis AJ, Rioux TP, Potter AW. Use of thermal mannequins for evaluation of heat stress imposed by personal protective equipment. In: Shiels B, Lehtonen K, editors. Performance of Protective Clothing and Equipment: 10th Volume, Risk Reduction through Research and Testing, ASTM STP1593. West Conshohocken, PA: ASTM International; 2016. pp. 286-296

[85] Potter AW, Gonzalez JA, Karis AJ, Santee WR, Rioux TP, Blanchard LA. Biophysical characteristics and measured wind effects of chemical protective ensembles with and without body armor. In: Technical Report,

T15-8; ADA#621169. Natick, MA, 01760, USA: US Army Research Institute of Environmental Medicine; 2015. Available from: www.dtic.mil/dtic/tr/ fulltext/u2/a621169.pdf

[86] American Society of Testing and Materials International (ASTM). Standard Test Method for Measuring the Thermal Insulation of Clothing Using a Heated Manikin (ASTM F1291-16) [Standard]. Philadelphia, Pa.: ASTM; 2016

[87] American Society of Testing and Materials International (ASTM). Standard Test Method for Measuring the Evaporative Resistance of Clothing Using a Sweating Manikin (ASTM F2370-16) [Standard]. Philadelphia, Pa.: ASTM; 2016

[88] Gagge AP, Burton AC, Bazett HC. A practical system of units for the description of the heat exchange of man with his environment. Science. 1941;**94**:428-430

[89] Woodcock AH. Moisture transfer in textile systems, Part I. Textile Research Journal. 1962;**32**(8):628-633

[90] Woodcock AH. Moisture permeability index—A new index for describing evaporative heat transfer through fabric systems. In: Technical Report (TR-EP-149). Natick, MA 01702, USA: Quartermaster Research and Engineering Command; 1961

[91] Potter AW, Gonzalez JA, Karis AJ, Rioux TP, Blanchard LA, Xu X. Impact of estimating thermal manikin derived wind velocity coefficients on physiological modeling. In: Technical Report, ADA#607972. Natick, MA, 01760, USA: US Army Research Institute of Environmental Medicine; 2014. Available from: www.dtic.mil/dtic/tr/ fulltext/u2/a607972.pdf

[92] Potter AW. Method for estimating evaporative potential (im/clo) from

ASTM standard single wind velocity measures. In: Technical Report, T16- 14, ADA#637325. Natick, MA, 01760, USA: US Army Research Institute of Environmental Medicine; 2016. Available from: www.dtic.mil/dtic/tr/ fulltext/u2/a637325.pdf

[93] Kraning KK II, Gonzalez RR. A mechanistic computer simulation of human work in heat that accounts for physical and physiological effects of clothing, aerobic fitness, and progressive dehydration. Journal of Thermal Biology. 1997;**22**(4):331-342

[94] Welles AP, Tharion WJ, Potter AW, Buller MJ. Novel method of estimating metabolic rates of soldiers engaged in chemical biological defense training. In: Technical Report, T17-02, ADA#1022691. Natick, MA, 01760, USA: US Army Research Institute of Environmental Medicine; 2017

[95] McCullough EA, BW J, Huck J. A data base for estimating clothing insulation. ASHRAE Transactions. 1985;**91**:29-47

[96] Al-ajmi FF, Loveday DL, Bedwell KH, Havenith G. Thermal insulation and clothing area factors of typical Arabian Gulf clothing ensembles for males and females: Measurements using thermal manikins. Applied Ergonomics. 2008;**39**:407-414

[97] ISO 9920:2007. Ergonomics of the thermal environment. Estimation of thermal and insulation and evaporative resistance of a clothing ensemble. Geneva: International Organisation for Standardisation; 2007

[98] Osczevski R, Bluestein M. The new wind chill equivalent temperature chart. Bulletin of the American Meteorological Society. 2005;**86**(10):1453-1458

[99] National Weather Service. Windchill Temperature Index. Office of

**67**

Natick; 2018

*Modeling Thermoregulatory Responses to Cold Environments*

reproductive hormones. Journal of Applied Physiology. 1999;**87**:381-385

[108] Charkoudian N, Stephens DP, Pirkle KC, Kosiba WA, Johnson JM. Influence of female reproductive hormones on local thermal control of skin blood flow. Journal of Applied Physiology. 1999;**87**:1719-1723

[109] Hodges GJ, Kosiba WA, Zhao K, Alvarez GE, Johnson JM. The role of baseline in the cutaneous vasoconstrictor responses during combined local and whole body cooling in humans. American Journal of Physiology Heart & Circulatory Physiology. 2007;**293**:H3187-H3192

[110] Johnson JM, Yen TC, Zhao K, Kosiba WA. Sympathetic, sensory, and nonneuronal contributions to the cutaneous vasoconstrictor response to local cooling. American Journal of Physiology Heart & Circulatory Physiology. 2005;**288**:H1573-H1579

[111] Stephens DP, Aoki K, Kosiba WA, Johnson JM. Nonnoradrenergic mechanism of reflex cutaneous vasoconstriction in men. American Journal of Physiology Heart & Circulatory Physiology. 2001;**280**:H1496-H1504

[112] Thompson CS, Holowatz LA, Kenney WL. Attenuated noradrenergic sensitivity during local cooling in aged human skin. Journal of Physiology.

2005;**564**:313-319

2004;**558**:697-704

2007;**293**:H30-H36

[113] Thompson CS, Kenney

[114] Thompson-Torgerson CS, Holowatz LA, Flavahan NA, Kenney WL. Rho kinase-mediated local coldinduced cutaneous vasoconstriction is augmented in aged human skin. American Journal of Physiology Heart & Circulatory Physiology.

WL. Altered neurotransmitter control of reflex vasoconstriction in aged human skin. Journal of Physiology.

*DOI: http://dx.doi.org/10.5772/intechopen.81238*

Climate, Water, and Weather Services. Washington, D.C.: National Oceanic and Atmospheric Administration; 2001

[100] Xu X, Tikuisis P. Thermoregulatory modeling for cold stress. Comprehensive

[101] Gonzalez RR, McLellan TM, Withey WR, Chang SK, KB P. Heat strain models applicable for protective

clothing systems: Comparison of core temperature response. Journal of Applied Physiology.

[102] Department of the Army and Air Force. In: Heat Stress Control and Heat Casualty Management. TB-MED 507. Washington, DC: Government Printing

[103] Institute of Medicine. Dietary Reference Intakes for Water, Potassium,

Sodium, Chloride, and Sulfate. Washington, DC: The National

[104] Holmér I. Required clothing insulation (IREQ ) as an analytical index of cold stress. ASHRAE Transactions.

[105] ISO 11079. Ergonomics of the thermal environment—determination and interpretation of cold stress when using required clothing insulation (IREQ ) and local cooling effects. Geneva: International Organisation for

[106] Potter AW, Gonzalez JA, Carter AJ, Looney DP, Rioux TP, Srinivasan S, et al. Comparison of Cold Weather Clothing Biophysical Properties: US Army, Canadian Department of National Defence, and Norwegian Military. United States: US Army Research Institute of Environmental Medicine

[107] Charkoudian N, Johnson JM. Reflex control of cutaneous vasoconstrictor system is reset by exogenous female

Academies Press; 2005

1984;**90**(6):1116-1128

Standardisation; 2007

Physiology. 2014;**4**:1-25

1997;**83**(3):1017-1032

Office; 2003

Climate, Water, and Weather Services. Washington, D.C.: National Oceanic and Atmospheric Administration; 2001

*Autonomic Nervous System Monitoring - Heart Rate Variability*

ASTM standard single wind velocity measures. In: Technical Report, T16- 14, ADA#637325. Natick, MA, 01760, USA: US Army Research Institute of Environmental Medicine; 2016. Available from: www.dtic.mil/dtic/tr/

[93] Kraning KK II, Gonzalez RR. A mechanistic computer simulation of human work in heat that accounts for physical and physiological effects of clothing, aerobic fitness, and progressive dehydration. Journal of Thermal Biology. 1997;**22**(4):331-342

[94] Welles AP, Tharion WJ, Potter AW, Buller MJ. Novel method of estimating metabolic rates of soldiers engaged in chemical biological

defense training. In: Technical Report, T17-02, ADA#1022691. Natick, MA, 01760, USA: US Army Research Institute of Environmental Medicine;

[95] McCullough EA, BW J, Huck J. A data base for estimating clothing insulation. ASHRAE Transactions.

[96] Al-ajmi FF, Loveday DL, Bedwell KH, Havenith G. Thermal insulation and clothing area factors of typical Arabian Gulf clothing ensembles for males and females: Measurements using thermal manikins. Applied Ergonomics.

[97] ISO 9920:2007. Ergonomics of the thermal environment. Estimation of thermal and insulation and evaporative resistance of a clothing ensemble. Geneva: International Organisation for

[98] Osczevski R, Bluestein M. The new wind chill equivalent temperature chart. Bulletin of the American Meteorological

Windchill Temperature Index. Office of

Society. 2005;**86**(10):1453-1458

[99] National Weather Service.

fulltext/u2/a637325.pdf

2017

1985;**91**:29-47

2008;**39**:407-414

Standardisation; 2007

T15-8; ADA#621169. Natick, MA, 01760, USA: US Army Research Institute of Environmental Medicine; 2015. Available from: www.dtic.mil/dtic/tr/

[86] American Society of Testing and Materials International (ASTM).

[87] American Society of Testing and Materials International (ASTM). Standard Test Method for Measuring the Evaporative Resistance of Clothing Using a Sweating Manikin (ASTM F2370-16) [Standard]. Philadelphia, Pa.:

[88] Gagge AP, Burton AC, Bazett HC. A practical system of units for the description of the heat exchange of man with his environment. Science.

Journal. 1962;**32**(8):628-633

[90] Woodcock AH. Moisture

[89] Woodcock AH. Moisture transfer in textile systems, Part I. Textile Research

permeability index—A new index for describing evaporative heat transfer through fabric systems. In: Technical Report (TR-EP-149). Natick, MA 01702, USA: Quartermaster Research and Engineering Command; 1961

[91] Potter AW, Gonzalez JA, Karis AJ, Rioux TP, Blanchard LA, Xu X. Impact

[92] Potter AW. Method for estimating evaporative potential (im/clo) from

of estimating thermal manikin derived wind velocity coefficients on physiological modeling. In: Technical Report, ADA#607972. Natick, MA, 01760, USA: US Army Research Institute of Environmental Medicine; 2014. Available from: www.dtic.mil/dtic/tr/

fulltext/u2/a607972.pdf

Standard Test Method for Measuring the Thermal Insulation of Clothing Using a Heated Manikin (ASTM F1291-16) [Standard]. Philadelphia, Pa.: ASTM;

fulltext/u2/a621169.pdf

2016

ASTM; 2016

1941;**94**:428-430

**66**

[100] Xu X, Tikuisis P. Thermoregulatory modeling for cold stress. Comprehensive Physiology. 2014;**4**:1-25

[101] Gonzalez RR, McLellan TM, Withey WR, Chang SK, KB P. Heat strain models applicable for protective clothing systems: Comparison of core temperature response. Journal of Applied Physiology. 1997;**83**(3):1017-1032

[102] Department of the Army and Air Force. In: Heat Stress Control and Heat Casualty Management. TB-MED 507. Washington, DC: Government Printing Office; 2003

[103] Institute of Medicine. Dietary Reference Intakes for Water, Potassium, Sodium, Chloride, and Sulfate. Washington, DC: The National Academies Press; 2005

[104] Holmér I. Required clothing insulation (IREQ ) as an analytical index of cold stress. ASHRAE Transactions. 1984;**90**(6):1116-1128

[105] ISO 11079. Ergonomics of the thermal environment—determination and interpretation of cold stress when using required clothing insulation (IREQ ) and local cooling effects. Geneva: International Organisation for Standardisation; 2007

[106] Potter AW, Gonzalez JA, Carter AJ, Looney DP, Rioux TP, Srinivasan S, et al. Comparison of Cold Weather Clothing Biophysical Properties: US Army, Canadian Department of National Defence, and Norwegian Military. United States: US Army Research Institute of Environmental Medicine Natick; 2018

[107] Charkoudian N, Johnson JM. Reflex control of cutaneous vasoconstrictor system is reset by exogenous female

reproductive hormones. Journal of Applied Physiology. 1999;**87**:381-385

[108] Charkoudian N, Stephens DP, Pirkle KC, Kosiba WA, Johnson JM. Influence of female reproductive hormones on local thermal control of skin blood flow. Journal of Applied Physiology. 1999;**87**:1719-1723

[109] Hodges GJ, Kosiba WA, Zhao K, Alvarez GE, Johnson JM. The role of baseline in the cutaneous vasoconstrictor responses during combined local and whole body cooling in humans. American Journal of Physiology Heart & Circulatory Physiology. 2007;**293**:H3187-H3192

[110] Johnson JM, Yen TC, Zhao K, Kosiba WA. Sympathetic, sensory, and nonneuronal contributions to the cutaneous vasoconstrictor response to local cooling. American Journal of Physiology Heart & Circulatory Physiology. 2005;**288**:H1573-H1579

[111] Stephens DP, Aoki K, Kosiba WA, Johnson JM. Nonnoradrenergic mechanism of reflex cutaneous vasoconstriction in men. American Journal of Physiology Heart & Circulatory Physiology. 2001;**280**:H1496-H1504

[112] Thompson CS, Holowatz LA, Kenney WL. Attenuated noradrenergic sensitivity during local cooling in aged human skin. Journal of Physiology. 2005;**564**:313-319

[113] Thompson CS, Kenney WL. Altered neurotransmitter control of reflex vasoconstriction in aged human skin. Journal of Physiology. 2004;**558**:697-704

[114] Thompson-Torgerson CS, Holowatz LA, Flavahan NA, Kenney WL. Rho kinase-mediated local coldinduced cutaneous vasoconstriction is augmented in aged human skin. American Journal of Physiology Heart & Circulatory Physiology. 2007;**293**:H30-H36

[115] Wissler EH. A quantitative assessment of skin blood flow in humans. European Journal of Applied Physiology. 2008;**104**:145-157

[116] Cooper KE, Edholm OG, Mottram RF. The blood flow in skin and muscle of the human forearm. The Journal of Physiology. 1955;**128**(2):258-267

[117] Nadel ER, Horvath SM, Dawson CA, Tucker A. Sensitivity to central and peripheral thermal stimulation in man. Journal of Applied Physiology. 1970;**29**:603-609

[118] Timbal J, Boutelier C, Loncle M, Bougues L. Comparison of shivering in man exposed to cold in water and in air. Pflügers Archiv. 1976;**365**:243-248

[119] Hayward JS, Eckerson JD, Collis ML. Thermoregulatory heat production in man: Prediction equation based on skin and core temperatures. Journal of Applied Physiology. 1977;**42**:377-384

[120] Tikuisis P, Giesbrecht GG. Prediction of shivering heat production from core and mean skin temperatures. European Journal of Applied Physiology and Occupational Physiology. 1999;**79**:221-229

[121] Parsons R. ASHRAE Handbook— Fundamentals. Atlanta, GA: American Society of Heating, Refrigerating and Air-conditioning Engineers; 1997

[122] Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, et al. Compendium of physical activities: An update of activity codes and MET intensities. Medicine & Science in Sports & Exercise. 2000;**32**(suppl. 1):S498-S504

[123] Richmond PW, Potter AW, Looney DP, Santee WR. Terrain coefficients for predicting energy costs of walking over snow. Applied Ergonomics. 2019;**74**:48-54

[124] Looney DP, Potter AW, Pryor JL, Bremmer PE, Chalmers CR, McCLung HL, et al. Metabolic costs of standing and walking in healthy adults: A metaegression. Medicine & Science in Sports & Exercise. 2019;**51**(2)

[125] American College of Sports Medicine. ACSM's Guidelines for Exercise Testing and Prescription. Philadelphia, PA: Lippincott Williams & Wilkins; 2013

[126] Balogun JA, Martin DA, Clendenin MA. Human energy expenditure during level walking on a treadmill at speeds of 54-130 m min-1. International Disability Studies. 1989;**11**(2):71-74

[127] Browning RC, Reynolds MM, Board WJ, Walters KA, Reiser RF. Obesity does not impair walking economy across a range of speeds and grades. Journal of Applied Physiology. 2013;**114**(9):1125-1131

[128] Pandolf KB, Givoni B, Goldman RF. Predicting energy expenditure with loads while standing or walking very slowly. Journal of Applied Physiology. 1977;**43**(4):577-581

[129] Workman JM, Armstrong BW. Metabolic cost of walking: Equation and model. Journal of Applied Physiology. 1986;**61**(4):1369-1374

[130] Santee WR. Windchill index and military applications. Aviation, Space, and Environmental Medicine. 2002;**73**:699-702

[131] Santee WR, Reardon MJ, Pandolf KB. Modeling the physiological and medical effects of exposure to environmental extremes. In: Friedl KE, Santee WR, editors. Military Quantitative Physiology: Problems and Concepts in Military Operational Medicine. Fort Detrick, MD: Office of The Surgeon General United States Army; 2012. pp. 39-72

**69**

*Modeling Thermoregulatory Responses to Cold Environments*

in the estimation of time of death. A review. Legal Medicine. 2012;**14**:55-62

[140] Smart JL, Kaliszan M. Use of a finite element model of heat transport in the human eye to predict time of death. Journal of Forensic Science.

[141] Besnard Y, Launay JC, Guinet-Lebreton A, Savourey G. PREDICTOL: A computer program to determine the thermophysiological duration limited exposures in various climatic conditions. Computer Methods and Programs in Biomedicine. 2004;**76**:221-228

[142] Xu X, Amin M, Santee

WR. Probability of Survival Decision Aid (PSDA). USARIEM T08/05, ADA478415. Natick, MA: US Army Research Institute of Environmental

[143] Keefe AA, Tikuisis P. A Guide to Making Stochastic and Single Point Predictions Using the Cold Exposure Survival Model (CESM). DRDC-TORONTO-TM-2008-061. Defence Research and Development Toronto

[144] Xu X, Allen A, Rioux T, Patel T, Sinha P, et al. Refinement of probability of survival decision aid (PSDA). In: Technical Note, TN14-02, ADA#599590. Natick, MA 01760 USA: U.S. Army Research Institute of Environmental

2013;**58**:S69-S77

Medicine; 2008

(Canada); 2008

Medicine; 2014

*DOI: http://dx.doi.org/10.5772/intechopen.81238*

[132] Castellani JW, O'Brien C, Baker-Fulco C, Sawka MN, Young AJ. Sustaining Health & Performance in Cold Weather Operations. USARIEM

TN/02-2, ADA 395745. Natick, MA: US Army Research Institute of Environmental Medicine; 2001

[133] Friedl KE. Predicting human limits—The special relationship between physiology research and the Army mission. In: Friedl KE, Santee WR, editors. Military Quantitative Physiology: Problems and Concepts in Military Operational Medicine: Problems and Concepts in Military Operational Medicine. Fort Detrick, MD: Office of The Surgeon General United States Army; 2012. pp. 1-38

[134] den Hartog EA, Lotens

WA. Postmortem time estimation using body temperature and a finite-element computer model. European Journal of Applied Physiology. 2004;**92**:734-737

[135] Mall G, Eisenmenger W. Estimation

of time since death by heat-flow finite-element model. Part I: Method, model, calibration and validation. Legal Medicine (Tokyo, Japan). 2005;**7**:1-14

W. Estimation of time since death by heat-flow finite-element model part II: Application to non-standard cooling conditions and preliminary results in practical casework. Legal Medicine (Tokyo, Japan). 2005;**7**:69-80

[136] Mall G, Eisenmenger

[137] Kanawaku Y, Kanetake J, Komiya A, Maruyama S, Funayama M. Computer simulation for

postmortem cooling processes in the outer ear. Legal Medicine. 2007;**9**:55-62

[138] Smart JL. Estimation of time of death with a fourier series unsteady state heat transfer model. Journal of Forensic

[139] Smart JL, Kaliszan M. The post mortem temperature plateau and its role

Science. 2010;**55**:1481-1487

*Modeling Thermoregulatory Responses to Cold Environments DOI: http://dx.doi.org/10.5772/intechopen.81238*

[132] Castellani JW, O'Brien C, Baker-Fulco C, Sawka MN, Young AJ. Sustaining Health & Performance in Cold Weather Operations. USARIEM TN/02-2, ADA 395745. Natick, MA: US Army Research Institute of Environmental Medicine; 2001

*Autonomic Nervous System Monitoring - Heart Rate Variability*

[124] Looney DP, Potter AW, Pryor JL, Bremmer PE, Chalmers CR, McCLung HL, et al. Metabolic costs of standing and walking in healthy adults: A metaegression. Medicine & Science in Sports

& Exercise. 2019;**51**(2)

Studies. 1989;**11**(2):71-74

2013;**114**(9):1125-1131

1977;**43**(4):577-581

2002;**73**:699-702

Army; 2012. pp. 39-72

[127] Browning RC, Reynolds MM, Board WJ, Walters KA, Reiser RF. Obesity does not impair walking economy across a range of speeds and grades. Journal of Applied Physiology.

[128] Pandolf KB, Givoni B, Goldman RF. Predicting energy expenditure with loads while standing or walking very slowly. Journal of Applied Physiology.

[129] Workman JM, Armstrong BW. Metabolic cost of walking: Equation and model. Journal of Applied Physiology. 1986;**61**(4):1369-1374

[130] Santee WR. Windchill index and military applications. Aviation, Space, and Environmental Medicine.

[131] Santee WR, Reardon MJ, Pandolf KB. Modeling the physiological and medical effects of exposure to environmental extremes. In: Friedl KE, Santee WR, editors. Military Quantitative Physiology: Problems and Concepts in Military Operational Medicine. Fort Detrick, MD: Office of The Surgeon General United States

Wilkins; 2013

[125] American College of Sports Medicine. ACSM's Guidelines for Exercise Testing and Prescription. Philadelphia, PA: Lippincott Williams &

[126] Balogun JA, Martin DA, Clendenin MA. Human energy expenditure during level walking on a treadmill at speeds of 54-130 m min-1. International Disability

[115] Wissler EH. A quantitative assessment of skin blood flow in humans. European Journal of Applied

Physiology. 2008;**104**:145-157

1970;**29**:603-609

[116] Cooper KE, Edholm OG, Mottram RF. The blood flow in skin and muscle of the human forearm. The Journal of Physiology. 1955;**128**(2):258-267

[117] Nadel ER, Horvath SM, Dawson CA, Tucker A. Sensitivity to central and peripheral thermal stimulation in man. Journal of Applied Physiology.

[118] Timbal J, Boutelier C, Loncle M, Bougues L. Comparison of shivering in man exposed to cold in water and in air. Pflügers Archiv. 1976;**365**:243-248

[119] Hayward JS, Eckerson JD, Collis ML. Thermoregulatory heat production in man: Prediction equation based on skin and core temperatures. Journal of Applied Physiology. 1977;**42**:377-384

[120] Tikuisis P, Giesbrecht GG. Prediction of shivering heat production from core and mean skin temperatures. European Journal of Applied Physiology and Occupational

Physiology. 1999;**79**:221-229

[121] Parsons R. ASHRAE Handbook— Fundamentals. Atlanta, GA: American Society of Heating, Refrigerating and Air-conditioning Engineers; 1997

[122] Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, et al. Compendium of physical activities: An update of activity codes and MET intensities. Medicine & Science in Sports & Exercise. 2000;**32**(suppl. 1):S498-S504

[123] Richmond PW, Potter AW, Looney DP, Santee WR. Terrain coefficients for predicting energy costs of walking over snow. Applied Ergonomics.

**68**

2019;**74**:48-54

[133] Friedl KE. Predicting human limits—The special relationship between physiology research and the Army mission. In: Friedl KE, Santee WR, editors. Military Quantitative Physiology: Problems and Concepts in Military Operational Medicine: Problems and Concepts in Military Operational Medicine. Fort Detrick, MD: Office of The Surgeon General United States Army; 2012. pp. 1-38

[134] den Hartog EA, Lotens WA. Postmortem time estimation using body temperature and a finite-element computer model. European Journal of Applied Physiology. 2004;**92**:734-737

[135] Mall G, Eisenmenger W. Estimation of time since death by heat-flow finite-element model. Part I: Method, model, calibration and validation. Legal Medicine (Tokyo, Japan). 2005;**7**:1-14

[136] Mall G, Eisenmenger W. Estimation of time since death by heat-flow finite-element model part II: Application to non-standard cooling conditions and preliminary results in practical casework. Legal Medicine (Tokyo, Japan). 2005;**7**:69-80

[137] Kanawaku Y, Kanetake J, Komiya A, Maruyama S, Funayama M. Computer simulation for postmortem cooling processes in the outer ear. Legal Medicine. 2007;**9**:55-62

[138] Smart JL. Estimation of time of death with a fourier series unsteady state heat transfer model. Journal of Forensic Science. 2010;**55**:1481-1487

[139] Smart JL, Kaliszan M. The post mortem temperature plateau and its role in the estimation of time of death. A review. Legal Medicine. 2012;**14**:55-62

[140] Smart JL, Kaliszan M. Use of a finite element model of heat transport in the human eye to predict time of death. Journal of Forensic Science. 2013;**58**:S69-S77

[141] Besnard Y, Launay JC, Guinet-Lebreton A, Savourey G. PREDICTOL: A computer program to determine the thermophysiological duration limited exposures in various climatic conditions. Computer Methods and Programs in Biomedicine. 2004;**76**:221-228

[142] Xu X, Amin M, Santee WR. Probability of Survival Decision Aid (PSDA). USARIEM T08/05, ADA478415. Natick, MA: US Army Research Institute of Environmental Medicine; 2008

[143] Keefe AA, Tikuisis P. A Guide to Making Stochastic and Single Point Predictions Using the Cold Exposure Survival Model (CESM). DRDC-TORONTO-TM-2008-061. Defence Research and Development Toronto (Canada); 2008

[144] Xu X, Allen A, Rioux T, Patel T, Sinha P, et al. Refinement of probability of survival decision aid (PSDA). In: Technical Note, TN14-02, ADA#599590. Natick, MA 01760 USA: U.S. Army Research Institute of Environmental Medicine; 2014

**71**

**Chapter 5**

Adults

**Abstract**

*Jonathan V. Roth*

improve patient outcome.

**1. Background**

Techniques to Reduce the

Magnitude and Duration of

Redistribution Hypothermia in

While much effort has been devoted to correcting intraoperative hypothermia and documenting the adverse outcomes associated with hypothermia, less attention has been directed to preventing redistribution hypothermia in the first place. Methods currently exist that can reduce the magnitude of redistribution hypothermia, but are not widely practiced. This chapter focuses on the pathophysiology of redistribution hypothermia and the currently available methods that can be employed to reduce redistribution hypothermia. Additional promising, but currently unproven, methods are discussed. Since hypothermia causes adverse outcomes, it is anticipated that the reduction in redistribution hypothermia will

**Keywords:** redistribution hypothermia, hypothermia, perioperative hypothermia,

Hypothermia has multiple adverse consequences and should be avoided (**Table 1**) [1, 2]. The Anesthesia Patient Safety Foundation has recently reaffirmed that even mild hypothermia is associated with an increase in complications [3]. In studies assessing whether patients were hypothermic, typically the end-of-case temperature has been used for this determination and its association with complications. With the exception of one study where there was increased blood loss at 36.5°C [4], an increase in complications occurs when the end-of-case temperature is <36.0°C. However, there is increasing recognition that intraoperative temperature matters. The American College of Surgeons consider intraoperative hypothermia to be a modifiable risk factor for surgical site infections; they recommend the maintenance of intraoperative normothermia and the use of prewarming [5]. The 2017 Centers for Disease Control and Prevention (CDC)

intraoperative hypothermia, inhalation induction, anesthesia induction

guidelines recommend maintenance of perioperative normothermia [6].

While much effort has been devoted to documenting adverse outcomes and correcting intraoperative hypothermia, relatively little attention has been directed to preventing intraoperative hypothermia in the first place. "Despite Active Warming, Hypothermia Is Routine in the First Hour of Anesthesia" was written on the cover of the February 2015 issue of Anesthesiology. In a

#### **Chapter 5**

## Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults

*Jonathan V. Roth*

#### **Abstract**

While much effort has been devoted to correcting intraoperative hypothermia and documenting the adverse outcomes associated with hypothermia, less attention has been directed to preventing redistribution hypothermia in the first place. Methods currently exist that can reduce the magnitude of redistribution hypothermia, but are not widely practiced. This chapter focuses on the pathophysiology of redistribution hypothermia and the currently available methods that can be employed to reduce redistribution hypothermia. Additional promising, but currently unproven, methods are discussed. Since hypothermia causes adverse outcomes, it is anticipated that the reduction in redistribution hypothermia will improve patient outcome.

**Keywords:** redistribution hypothermia, hypothermia, perioperative hypothermia, intraoperative hypothermia, inhalation induction, anesthesia induction

#### **1. Background**

Hypothermia has multiple adverse consequences and should be avoided (**Table 1**) [1, 2]. The Anesthesia Patient Safety Foundation has recently reaffirmed that even mild hypothermia is associated with an increase in complications [3]. In studies assessing whether patients were hypothermic, typically the end-of-case temperature has been used for this determination and its association with complications. With the exception of one study where there was increased blood loss at 36.5°C [4], an increase in complications occurs when the end-of-case temperature is <36.0°C. However, there is increasing recognition that intraoperative temperature matters. The American College of Surgeons consider intraoperative hypothermia to be a modifiable risk factor for surgical site infections; they recommend the maintenance of intraoperative normothermia and the use of prewarming [5]. The 2017 Centers for Disease Control and Prevention (CDC) guidelines recommend maintenance of perioperative normothermia [6].

While much effort has been devoted to documenting adverse outcomes and correcting intraoperative hypothermia, relatively little attention has been directed to preventing intraoperative hypothermia in the first place. "Despite Active Warming, Hypothermia Is Routine in the First Hour of Anesthesia" was written on the cover of the February 2015 issue of Anesthesiology. In a


#### **Table 1.**

*Complications of hypothermia*.

retrospective review, Sun et al. found 64% of 58,814 adult patients had a temperature measurement under 36.0°C after 45 min [7]. Some hypothermia complications occur intraoperatively (e.g., coagulopathy and increased transfusion requirements), some postoperatively (e.g., shivering and delayed emergence) and some likely both (e.g., infection risk). The contribution of intraoperative hypothermia to postoperative complications may often be unrecognized. For example, patients may have decreased immunologic defense against infection at the time of incision, that is, during the vulnerable period when infections can become established. It is plausible that, if redistribution hypothermia can be reduced, one may be able to reduce the intraoperative and postoperative complications associated with hypothermia, particularly in situations where patients are at increased risk of developing a greater degree of hypothermia or may have increased risk of hypothermia-associated complications (**Table 2**). End-of-case hypothermia implies intraoperative hypothermia. End-of-case normothermia does not imply intraoperative normothermia. A patient may have been hypothermic intraoperatively, having suffered the consequences of intraoperative hypothermia, achieving normothermia only at the end of the case.

The body contains three thermal zones: the core (abdomen, thorax, and brain), the periphery (the extremities), and the skin. At rest, the core temperature is 37.0°C (36.5–37.5°C) and the periphery is 2–4°C cooler. The skin temperature can approach ambient temperature. At rest, most of the basal heat production occurs in the core. Heat travels from the core to the periphery to the skin and out to the environment. In the steady state, the rate of heat loss equals the rate of heat production, and the heat content of the body remains the same. Since temperature is just a measurement that reflects heat content, the temperature remains the same. The body normally maintains core temperature within a narrow range. Within limits, the periphery can act as a temperature buffer as it can add or lose heat, changing its temperature, while keeping the core temperature within a narrow range. The core temperature is the temperature that is physiologically most important [8].

There are behavioral (e.g., seeking an environment of a different temperature and changing clothing) and physiologic defenses to thermal challenges. Under anesthesia only the physiologic defenses are available. As one becomes too warm, the first physiologic defense is to vasodilate. If the temperature increases further,

**73**

are impaired during anesthesia.

*DOI: http://dx.doi.org/10.5772/intechopen.80830*

Dynamic obstructive cardiomyopathies

Increased risk or consequence of infection

Foreign body placement (e.g., artificial joints)

Large exposure of tissues that have a propensity to bleed Hypercarbia exacerbating hypothermia-induced coagulopathy Increased risk of hypothermia due to patient characteristics

Inability or delay in warming patient or environment

Remote location with inability to adjust ambient temperature

Risk from hypothermia- induced vasoconstriction

*may have increased risk of hypothermia-associated complications.*

Coronary artery disease Stenotic valvular heart disease

Immunocompromised Colon surgery

Spine surgery Liver surgery Prostate resection

Elderly Frail

Lateral or prone positioning Other prolonged positioning

Axillary-bifemoral artery bypass

Warming devices not available

Raynaud's disease or syndrome

Free flap with arterial vascular anastomosis

Large surface area burn

Robotic surgery

Vascular surgery

**Table 2.**

*Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults*

Risk posed by postoperative hyperdynamic/tachycardic response to hypothermia

Potential for large blood loss increased by hypothermia- induced coagulopathy

the patient perspires. As one cools, the first defense is to vasoconstrict. If the temperature decreases further, the patient shivers [9]. These physiologic defenses

*Examples of situations where patients are at increased risk of developing a greater degree of hypothermia or* 

There is a large vascular supply to the periphery and skin, but at rest these vessels are relatively vasoconstricted and there is relatively little blood flow. The blood flow to the periphery and skin can increase if these blood vessels vasodilate because of the administration of a vasodilator (or there is an increased metabolic need such as what occurs during physical activity). If pharmacologic-induced vasodilation occurs, the increased blood flow to the periphery transfers more heat from the core to the periphery and skin. As a result, the core's temperature decreases while that of the periphery will increase. This process is called redistribution hypothermia. Since heat only travels from higher to lower temperature (second law of

*DOI: http://dx.doi.org/10.5772/intechopen.80830 Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults*


#### **Table 2.**

*Autonomic Nervous System Monitoring - Heart Rate Variability*

• Increased financial cost of care of hypothermia complications

• Surgical wound infection

• Delayed wake-up • Prolonged PACU stays

**Table 1.**

• Patient discomfort, postoperative shivering • More likely to require postoperative ventilation

• Adverse respiratory events in PACU

• Increased hospital length of stay • Negative nitrogen balance • Delayed wound healing

• Failure to meet MACRA standard

*Complications of hypothermia*.

• Morbid cardiac events (ischemia, infarctions, arrhythmias, sympathetic activation)

• Coagulopathy, increased blood loss, increased transfusion requirements

retrospective review, Sun et al. found 64% of 58,814 adult patients had a temperature measurement under 36.0°C after 45 min [7]. Some hypothermia complications occur intraoperatively (e.g., coagulopathy and increased transfusion requirements), some postoperatively (e.g., shivering and delayed emergence) and some likely both (e.g., infection risk). The contribution of intraoperative hypothermia to postoperative complications may often be unrecognized. For example, patients may have decreased immunologic defense against infection at the time of incision, that is, during the vulnerable period when infections can become established. It is plausible that, if redistribution hypothermia can be reduced, one may be able to reduce the intraoperative and postoperative complications associated with hypothermia, particularly in situations where patients are at increased risk of developing a greater degree of hypothermia or may have increased risk of hypothermia-associated complications (**Table 2**). End-of-case hypothermia implies intraoperative hypothermia. End-of-case normothermia does not imply intraoperative normothermia. A patient may have been hypothermic intraoperatively, having suffered the consequences of intraoperative

hypothermia, achieving normothermia only at the end of the case.

the temperature that is physiologically most important [8].

The body contains three thermal zones: the core (abdomen, thorax, and brain), the periphery (the extremities), and the skin. At rest, the core temperature is 37.0°C (36.5–37.5°C) and the periphery is 2–4°C cooler. The skin temperature can approach ambient temperature. At rest, most of the basal heat production occurs in the core. Heat travels from the core to the periphery to the skin and out to the environment. In the steady state, the rate of heat loss equals the rate of heat production, and the heat content of the body remains the same. Since temperature is just a measurement that reflects heat content, the temperature remains the same. The body normally maintains core temperature within a narrow range. Within limits, the periphery can act as a temperature buffer as it can add or lose heat, changing its temperature, while keeping the core temperature within a narrow range. The core temperature is

There are behavioral (e.g., seeking an environment of a different temperature and changing clothing) and physiologic defenses to thermal challenges. Under anesthesia only the physiologic defenses are available. As one becomes too warm, the first physiologic defense is to vasodilate. If the temperature increases further,

**72**

*Examples of situations where patients are at increased risk of developing a greater degree of hypothermia or may have increased risk of hypothermia-associated complications.*

the patient perspires. As one cools, the first defense is to vasoconstrict. If the temperature decreases further, the patient shivers [9]. These physiologic defenses are impaired during anesthesia.

There is a large vascular supply to the periphery and skin, but at rest these vessels are relatively vasoconstricted and there is relatively little blood flow. The blood flow to the periphery and skin can increase if these blood vessels vasodilate because of the administration of a vasodilator (or there is an increased metabolic need such as what occurs during physical activity). If pharmacologic-induced vasodilation occurs, the increased blood flow to the periphery transfers more heat from the core to the periphery and skin. As a result, the core's temperature decreases while that of the periphery will increase. This process is called redistribution hypothermia. Since heat only travels from higher to lower temperature (second law of

thermodynamics), the heat in the periphery cannot be transferred back to the core. However, warming the periphery decreases the temperature gradient between the core and periphery. A smaller temperature gradient reduces the rate of heat transfer from the core [10]. Thus, more of the heat produced in the core will remain in the core, thus contributing to increasing the core temperature or decreasing the rate of core temperature decrease. If the periphery is warmed to a temperature greater than the core, heat can be transferred from the periphery to the core.

Propofol administration causes vasodilation and thus redistribution hypothermia. Propofol inductions typically result in a decrease in core temperature of about 1.5°C [11–13]. While there is also heat loss to the environment (via conduction, convection, radiation, evaporation, and airway losses), redistribution hypothermia is the major reason for the core temperature decrease in the first 15–60 min of an anesthetic. Although not specified in Sun's results, because propofol is the most common method of anesthetic induction in developed nations, it is likely most of these patients were induced with intravenous propofol and can explain the 64% incidence hypothermia (core temperature < 36.0°C) found in his review [7].

With this understanding, the following physiologic strategies have been studied to reduce redistribution hypothermia: (1) reduce the increased blood flow to the periphery and skin, (2) prewarm the periphery and skin, (3) increase metabolic activity, and (4) warm the environment. This chapter will discuss actual and potential methods available to reduce the magnitude and duration of redistribution hypothermia in adults.

#### **2. Studied methods to reduce redistribution hypothermia**

#### **2.1 Reducing the increased blood flow to the periphery and skin**

#### *2.1.1 Etomidate*

Compared to propofol, etomidate inductions result in a lesser initial temperature drop (1.4 vs. 0.5°C) [12]. Because of the adrenal axis suppression resulting from etomidate [14], the author does not recommend using etomidate just for thermal stability. However, if etomidate is used for other indications, one would expect a thermal benefit.

#### *2.1.2 Ketamine*

Compared to propofol, ketamine inductions result in a lesser initial temperature drop (1.5 vs. 0.9°C) [13]. Because of the risk of emergence reactions and hallucinations from an anesthetic dose of ketamine [15], the author does not recommend using ketamine just for thermal stability. However, if an anesthetic dose of ketamine is used for other indications, one would expect a thermal benefit.

#### *2.1.3 Phenylephrine infusion*

Ikeda et al. have demonstrated that a phenylephrine infusion of 0.5 mcg/kg/ min starting immediately before induction with 2.5 mg/kg propofol results in an initial lower temperature decrease compared to propofol after the first hour (1.2 vs. 0.5°C decrease after 1 h) [16]. Presumably the vasoconstriction from phenylephrine opposes the vasodilation resulting from propofol administration. In addition, the patients who received the phenylephrine infusion maintained a higher mean arterial

**75**

*DOI: http://dx.doi.org/10.5772/intechopen.80830*

hypothesis requires investigation.)

*2.1.4 Phenylephrine bolus*

thermal benefit.

*2.1.5 Inhalation inductions*

*Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults*

blood pressure (83 ± 9 vs. 72 ± 8 mm Hg, mean ± SD). (It seems plausible that any technique discussed in this section that reduces vasodilation has the potential to accrue an additional benefit of reducing induction-associated hypotension. This

A 160 mcg bolus of phenylephrine immediately prior to 2.2 mg/kg propofol reduces the mean decrease in core temperature by about 0.43°C in the first hour than those who did not receive the phenylephrine bolus [17, 18]. While redistribution hypothermia can continue for up to 3 h, a large part of the temperature decrease occurs within the first 15 min. The vasoconstricting effect of a bolus of phenylephrine lasts sufficiently long to oppose much of the maximal vasodilation resulting from propofol induction. While most patients decrease their blood pressure after propofol administration, the bolus phenylephrine reduced the incidence of propofolinduced hypotension from 98 to 58% [17, 18]. While generally effective, the 160 mcg dose was used on all patients in this study but may not be optimal. Some patients still became hypotensive (systolic BP < 85 mm Hg), and 1 patient in this group of 50 patients increased the systolic blood pressure to >180 mm Hg [17, 18]. It remains to be determined if a weight-based dose could be found that further reduces the incidence of hypotension, avoids dangerous hypertension, and still maintains the

Ikeda et al. demonstrated less core hypothermia when anesthesia is induced with inhaled sevoflurane than with intravenous propofol (1.5 vs. 0.8 °C decrease after 1 h) [11]. This study of 10 patients in each group was done at a time when the concept of redistribution hypothermia was still in development and the harmful effects of even mild hypothermia were not as well appreciated as they are today. A recent study (50 patients in each of six groups) replicated and strengthened these findings [17, 18]. Inhalation inductions of 8% sevoflurane in either 100% oxygen or 50% oxygen/50% nitrous oxide resulted in a higher mean temperature by about 0.5°C than those who received 2.2 mg/kg propofol in patients aged 18–55 years [17, 18]. Inhalation inductions were also found effective in reducing redistribution hypothermia in older (56–88 years, mean 67.2 years) patients. Elderly patients have an increased risk for hypothermia [19–21] for reasons that include decreased metabolic activity, decreased muscle mass, an impaired vasoconstriction response, and an impaired shivering response. A previous study also concluded that inhalation induction is more hemodynamically stable than IV propofol inductions [22]. In contrast to propofol inductions where significant hypotension can occur immediately, an inhalation induction typically causes a more gradual decrease in blood

pressure which can be treated before severe hypotension develops.

33% chose IV induction, and 17% were undecided [24].

In adults, anesthetic inductions are achieved most commonly by intravenous, not inhalation, inductions for reasons that include inhalation inductions take extra time, room contamination with anesthetic gases, and possible patient dissatisfaction. An inhalation induction takes 1–2 min longer than an intravenous induction [17, 18] and that lost time may be recovered by a quicker wake-up because of the patient being warmer. However, Muzi et al. demonstrated that the speed of inhalation induction approached that of an intravenous induction using a primed circuit [23]. Although many anesthesia practitioners may assume patients would not want the inhalation technique, when offered a choice, 50% chose an inhalation induction,

#### *DOI: http://dx.doi.org/10.5772/intechopen.80830 Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults*

blood pressure (83 ± 9 vs. 72 ± 8 mm Hg, mean ± SD). (It seems plausible that any technique discussed in this section that reduces vasodilation has the potential to accrue an additional benefit of reducing induction-associated hypotension. This hypothesis requires investigation.)

#### *2.1.4 Phenylephrine bolus*

*Autonomic Nervous System Monitoring - Heart Rate Variability*

the core, heat can be transferred from the periphery to the core.

**2. Studied methods to reduce redistribution hypothermia**

**2.1 Reducing the increased blood flow to the periphery and skin**

thermodynamics), the heat in the periphery cannot be transferred back to the core. However, warming the periphery decreases the temperature gradient between the core and periphery. A smaller temperature gradient reduces the rate of heat transfer from the core [10]. Thus, more of the heat produced in the core will remain in the core, thus contributing to increasing the core temperature or decreasing the rate of core temperature decrease. If the periphery is warmed to a temperature greater than

Propofol administration causes vasodilation and thus redistribution hypothermia. Propofol inductions typically result in a decrease in core temperature of about 1.5°C [11–13]. While there is also heat loss to the environment (via conduction, convection, radiation, evaporation, and airway losses), redistribution hypothermia is the major reason for the core temperature decrease in the first 15–60 min of an anesthetic. Although not specified in Sun's results, because propofol is the most common method of anesthetic induction in developed nations, it is likely most of these patients were induced with intravenous propofol and can explain the 64% incidence hypothermia (core temperature < 36.0°C) found in

With this understanding, the following physiologic strategies have been studied to reduce redistribution hypothermia: (1) reduce the increased blood flow to the periphery and skin, (2) prewarm the periphery and skin, (3) increase metabolic activity, and (4) warm the environment. This chapter will discuss actual and potential methods available to reduce the magnitude and duration of redistribution

Compared to propofol, etomidate inductions result in a lesser initial temperature

Compared to propofol, ketamine inductions result in a lesser initial temperature drop (1.5 vs. 0.9°C) [13]. Because of the risk of emergence reactions and hallucinations from an anesthetic dose of ketamine [15], the author does not recommend using ketamine just for thermal stability. However, if an anesthetic dose of ketamine is used for other indications, one would expect a thermal benefit.

Ikeda et al. have demonstrated that a phenylephrine infusion of 0.5 mcg/kg/ min starting immediately before induction with 2.5 mg/kg propofol results in an initial lower temperature decrease compared to propofol after the first hour (1.2 vs. 0.5°C decrease after 1 h) [16]. Presumably the vasoconstriction from phenylephrine opposes the vasodilation resulting from propofol administration. In addition, the patients who received the phenylephrine infusion maintained a higher mean arterial

drop (1.4 vs. 0.5°C) [12]. Because of the adrenal axis suppression resulting from etomidate [14], the author does not recommend using etomidate just for thermal stability. However, if etomidate is used for other indications, one would expect a

**74**

his review [7].

*2.1.1 Etomidate*

thermal benefit.

*2.1.2 Ketamine*

*2.1.3 Phenylephrine infusion*

hypothermia in adults.

A 160 mcg bolus of phenylephrine immediately prior to 2.2 mg/kg propofol reduces the mean decrease in core temperature by about 0.43°C in the first hour than those who did not receive the phenylephrine bolus [17, 18]. While redistribution hypothermia can continue for up to 3 h, a large part of the temperature decrease occurs within the first 15 min. The vasoconstricting effect of a bolus of phenylephrine lasts sufficiently long to oppose much of the maximal vasodilation resulting from propofol induction. While most patients decrease their blood pressure after propofol administration, the bolus phenylephrine reduced the incidence of propofolinduced hypotension from 98 to 58% [17, 18]. While generally effective, the 160 mcg dose was used on all patients in this study but may not be optimal. Some patients still became hypotensive (systolic BP < 85 mm Hg), and 1 patient in this group of 50 patients increased the systolic blood pressure to >180 mm Hg [17, 18]. It remains to be determined if a weight-based dose could be found that further reduces the incidence of hypotension, avoids dangerous hypertension, and still maintains the thermal benefit.

#### *2.1.5 Inhalation inductions*

Ikeda et al. demonstrated less core hypothermia when anesthesia is induced with inhaled sevoflurane than with intravenous propofol (1.5 vs. 0.8 °C decrease after 1 h) [11]. This study of 10 patients in each group was done at a time when the concept of redistribution hypothermia was still in development and the harmful effects of even mild hypothermia were not as well appreciated as they are today. A recent study (50 patients in each of six groups) replicated and strengthened these findings [17, 18]. Inhalation inductions of 8% sevoflurane in either 100% oxygen or 50% oxygen/50% nitrous oxide resulted in a higher mean temperature by about 0.5°C than those who received 2.2 mg/kg propofol in patients aged 18–55 years [17, 18]. Inhalation inductions were also found effective in reducing redistribution hypothermia in older (56–88 years, mean 67.2 years) patients. Elderly patients have an increased risk for hypothermia [19–21] for reasons that include decreased metabolic activity, decreased muscle mass, an impaired vasoconstriction response, and an impaired shivering response. A previous study also concluded that inhalation induction is more hemodynamically stable than IV propofol inductions [22]. In contrast to propofol inductions where significant hypotension can occur immediately, an inhalation induction typically causes a more gradual decrease in blood pressure which can be treated before severe hypotension develops.

In adults, anesthetic inductions are achieved most commonly by intravenous, not inhalation, inductions for reasons that include inhalation inductions take extra time, room contamination with anesthetic gases, and possible patient dissatisfaction. An inhalation induction takes 1–2 min longer than an intravenous induction [17, 18] and that lost time may be recovered by a quicker wake-up because of the patient being warmer. However, Muzi et al. demonstrated that the speed of inhalation induction approached that of an intravenous induction using a primed circuit [23]. Although many anesthesia practitioners may assume patients would not want the inhalation technique, when offered a choice, 50% chose an inhalation induction, 33% chose IV induction, and 17% were undecided [24].

Inhalation inductions are not for everyone. Medical contraindications would include concern of increased intracranial pressure, indication for hypothermia, contraindication to hyperthermia (e.g., multiple sclerosis), increased aspiration risk, unfavorable airway anatomy, and patient fear of face masks. Since patients may lighten more rapidly when the face mask is removed for endotracheal intubation than with propofol, it may be prudent to avoid inhalation inductions when intubation may be a more prolonged process as there may potentially be an increased risk of awareness than a propofol induction. Examples would include inserting double-lumen tubes or training novice laryngoscopists.

However, there are additional potential benefits to preforming inhalation inductions. First, there will be no pain on propofol injection. Second, trainees will get more practice with airway management. In current practice, most patients after IV induction immediately receive a laryngeal mask airway (LMA) or endotracheal intubation. Third, future propofol shortages can be mitigated by employing inhalation inductions. Fourth, LMAs may be easier to insert while patients are breathing spontaneously as the airway tends to open during inspiration and there is less of an obstruction to proper LMA positioning than a totally collapsed airway one typically gets after IV propofol inductions. Fifth, there will be less second-hand exposure to propofol, currently a candidate factor in propofol addiction. Sixth, inhalation inductions may be a superior alternative over other induction agents to patients with allergies to propofol. Seventh, with intravenous inductions, atelectasis develops very quickly. One would expect that with spontaneous ventilation, there may be less atelectasis, but this will need to be studied. In patients breathing spontaneously via an LMA after IV propofol induction, one does not have to manage a patient who becomes apneic, thus eliminating extra tasks and saving time while starting a case. Lastly, propofol supports bacterial growth [25]. There is an increased number of colony-forming units in the stopcocks of patients who received propofol (10× at 24 h and >100× at 48 h) compared to those who did not [26]. While it is not established that this is a cause of increased infections, the avoidance of propofol would eliminate this as a concern. Removing the stopcocks could also address this concern but that adds cost and likely would not be universally done.

#### *2.1.6 Nitrous oxide*

Previous work suggests an ongoing thermal benefit to using nitrous oxide. Ozaki et al. found nitrous oxide impairs thermoregulation less than sevoflurane or isoflurane [27]. The threshold for vasoconstriction was 35.8 ± 0.3°C (mean ± SD) in the patients given 50% nitrous oxide combined with 0.5 MAC sevoflurane, which was statistically significantly greater than that in those given 1.0 MAC sevoflurane: 35.1 ± 0.4°C. Similarly, the threshold for vasoconstriction was 35.9 ± 0.3°C in the patients given 60% nitrous oxide combined with 0.5 MAC isoflurane, which was statistically significantly greater than that in those given 1.0 MAC isoflurane: 35.0 ± 0.5°C. The use of nitrous oxide allows for the thermal defense of vasoconstriction to activate before the patient becomes more hypothermic.

Nitrous oxide has been under challenge for several decades. Two of the reasons why nitrous oxide has been out of favor with many practitioners have been the concern of major cardiovascular morbidity and mortality and an increased risk of surgical site infections (SSI). In combination with another retrospective study of 49,016 patients where nitrous oxide use was associated with decreased 30-day mortality and decreased in-hospital mortality/morbidity, the results of the ENIGMA II have essentially eliminated these concerns [28–31]. ENIGMA II concludes "Our findings support the safety profile of nitrous oxide use in major noncardiac surgery. Nitrous oxide did not increase the risk of death and cardiovascular complications or surgical site infection, the emetogenic effect of nitrous oxide can

**77**

*DOI: http://dx.doi.org/10.5772/intechopen.80830*

be a valid reason to avoid nitrous oxide."

**2.2 Prewarm the periphery and skin**

effective in reducing hypothermia and shivering [44].

*Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults*

be controlled with antiemetic prophylaxis, and a desired effect of reduced volatile agent use was shown." [4] The other major reason for not using nitrous oxide has been the concern for postoperative nausea and vomiting (PONV). If a patient has been administered an antiemetic, there is a small nonsignificant increased risk of severe PONV. ENIGMA II concludes "Nitrous oxide increases the risk of severe PONV by only a small percentage, and the increased risk is essentially eliminated by antiemetic drug prophylaxis. Concern about severe PONV thus does not appear to

Except for potential environmental concerns, there is little reason not to use nitrous oxide in cases that are not of long duration (>4–6 h) unless there are physical contraindications (e.g., gas space expansion). Besides from its potential thermal benefit, nitrous oxide has been shown to reduce chronic pain in specific populations (Asians and other patients with variants in the methylenetetrahydrofolate reductase gene) [32]. The United States is in the midst of an opioid epidemic. The majority of heroin users got their start from medically prescribed opioids [33]. Nitrous oxide also has analgesic efficacy and may reduce intraoperative opioid use. Further research is needed, but the possibility of reducing chronic pain and intraoperative

Prewarming is the active warming of the body surface, often via forced-air warming, prior to induction of general or central neuraxial anesthesia. It is currently the most effective method of reducing redistribution hypothermia. It has been extensively studied, and, in addition to demonstrating warmer core temperatures, improved outcomes (decreased blood loss, transfusion requirement, and infection rate) have been demonstrated. (A recent chapter reviews much of the relevant detail and will not be repeated here [10]. A small representative sample of studies are listed [35–39].) Prewarming is fundamentally different from all other techniques in that it's the only technique that exogenously adds heat content to the patient. However, the technique is not universally used [40]. Obstacles to its use include (1) requirement of space, equipment, supplies, and personnel time, (2) change in the pattern of patient flow, (3) patient refusal or intolerance, (4) requirement of cleaning if reusable equipment is utilized, (5) insufficient availability of a power supply, (6) requirement to train personnel, (7) bypass of the holding area, (8) additional equipment maintenance requirement, and (9) inadequate knowledge of the value of prewarming [10]. Prewarming works by adding heat content to the periphery. This decreases the temperature gradient between core and periphery and thus decreases the heat transfer and redistribution hypothermia. Any method that can increase the peripheral temperature will reduce redistribution hypothermia. Any event that decreases peripheral temperature will increase redistribution. Thus, all reasonable efforts should be made to keep the periphery warm before induction of anesthesia. After application of forced-air warming, it will take time (usually 30 min) until an increase in core temperature occurs [41, 42]. This delay occurs because the periphery needs to be warmed before there is a significant effect on core temperature. The efficacy of prewarming can be limited by sweating, thermal discomfort, and efficacy of the warming device. Sessler et al. found that 30 min of prewarming increased peripheral tissue heat content by more than the amount normally distributed during the first hour of anesthesia [43]. Since there are other and ongoing mechanisms of heat loss, prewarming more than 30 min will likely benefit many patients. However, if it is difficult to arrange for 30+ min of prewarming or the patient does not tolerate the longer durations, even 10–20 min of prewarming is

opioid use may have benefit in combatting the opioid epidemic [34].

#### *DOI: http://dx.doi.org/10.5772/intechopen.80830 Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults*

be controlled with antiemetic prophylaxis, and a desired effect of reduced volatile agent use was shown." [4] The other major reason for not using nitrous oxide has been the concern for postoperative nausea and vomiting (PONV). If a patient has been administered an antiemetic, there is a small nonsignificant increased risk of severe PONV. ENIGMA II concludes "Nitrous oxide increases the risk of severe PONV by only a small percentage, and the increased risk is essentially eliminated by antiemetic drug prophylaxis. Concern about severe PONV thus does not appear to be a valid reason to avoid nitrous oxide."

Except for potential environmental concerns, there is little reason not to use nitrous oxide in cases that are not of long duration (>4–6 h) unless there are physical contraindications (e.g., gas space expansion). Besides from its potential thermal benefit, nitrous oxide has been shown to reduce chronic pain in specific populations (Asians and other patients with variants in the methylenetetrahydrofolate reductase gene) [32]. The United States is in the midst of an opioid epidemic. The majority of heroin users got their start from medically prescribed opioids [33]. Nitrous oxide also has analgesic efficacy and may reduce intraoperative opioid use. Further research is needed, but the possibility of reducing chronic pain and intraoperative opioid use may have benefit in combatting the opioid epidemic [34].

#### **2.2 Prewarm the periphery and skin**

*Autonomic Nervous System Monitoring - Heart Rate Variability*

inserting double-lumen tubes or training novice laryngoscopists.

Inhalation inductions are not for everyone. Medical contraindications would include concern of increased intracranial pressure, indication for hypothermia, contraindication to hyperthermia (e.g., multiple sclerosis), increased aspiration risk, unfavorable airway anatomy, and patient fear of face masks. Since patients may lighten more rapidly when the face mask is removed for endotracheal intubation than with propofol, it may be prudent to avoid inhalation inductions when intubation may be a more prolonged process as there may potentially be an increased risk of awareness than a propofol induction. Examples would include

However, there are additional potential benefits to preforming inhalation inductions. First, there will be no pain on propofol injection. Second, trainees will get more practice with airway management. In current practice, most patients after IV induction immediately receive a laryngeal mask airway (LMA) or endotracheal intubation. Third, future propofol shortages can be mitigated by employing inhalation inductions. Fourth, LMAs may be easier to insert while patients are breathing spontaneously as the airway tends to open during inspiration and there is less of an obstruction to proper LMA positioning than a totally collapsed airway one typically gets after IV propofol inductions. Fifth, there will be less second-hand exposure to propofol, currently a candidate factor in propofol addiction. Sixth, inhalation inductions may be a superior alternative over other induction agents to patients with allergies to propofol. Seventh, with intravenous inductions, atelectasis develops very quickly. One would expect that with spontaneous ventilation, there may be less atelectasis, but this will need to be studied. In patients breathing spontaneously via an LMA after IV propofol induction, one does not have to manage a patient who becomes apneic, thus eliminating extra tasks and saving time while starting a case. Lastly, propofol supports bacterial growth [25]. There is an increased number of colony-forming units in the stopcocks of patients who received propofol (10× at 24 h and >100× at 48 h) compared to those who did not [26]. While it is not established that this is a cause of increased infections, the avoidance of propofol would eliminate this as a concern. Removing the stopcocks could also address this concern but that adds cost and likely would not be universally done.

Previous work suggests an ongoing thermal benefit to using nitrous oxide. Ozaki et al. found nitrous oxide impairs thermoregulation less than sevoflurane or isoflurane [27]. The threshold for vasoconstriction was 35.8 ± 0.3°C (mean ± SD) in the patients given 50% nitrous oxide combined with 0.5 MAC sevoflurane, which was statistically significantly greater than that in those given 1.0 MAC sevoflurane: 35.1 ± 0.4°C. Similarly, the threshold for vasoconstriction was 35.9 ± 0.3°C in the patients given 60% nitrous oxide combined with 0.5 MAC isoflurane, which was statistically significantly greater than that in those given 1.0 MAC isoflurane: 35.0 ± 0.5°C. The use of nitrous oxide allows for the thermal defense of vasocon-

Nitrous oxide has been under challenge for several decades. Two of the reasons why nitrous oxide has been out of favor with many practitioners have been the concern of major cardiovascular morbidity and mortality and an increased risk of surgical site infections (SSI). In combination with another retrospective study of 49,016 patients where nitrous oxide use was associated with decreased 30-day mortality and decreased in-hospital mortality/morbidity, the results of the ENIGMA II have essentially eliminated these concerns [28–31]. ENIGMA II concludes "Our findings support the safety profile of nitrous oxide use in major noncardiac surgery. Nitrous oxide did not increase the risk of death and cardiovascular complications or surgical site infection, the emetogenic effect of nitrous oxide can

striction to activate before the patient becomes more hypothermic.

**76**

*2.1.6 Nitrous oxide*

Prewarming is the active warming of the body surface, often via forced-air warming, prior to induction of general or central neuraxial anesthesia. It is currently the most effective method of reducing redistribution hypothermia. It has been extensively studied, and, in addition to demonstrating warmer core temperatures, improved outcomes (decreased blood loss, transfusion requirement, and infection rate) have been demonstrated. (A recent chapter reviews much of the relevant detail and will not be repeated here [10]. A small representative sample of studies are listed [35–39].) Prewarming is fundamentally different from all other techniques in that it's the only technique that exogenously adds heat content to the patient. However, the technique is not universally used [40]. Obstacles to its use include (1) requirement of space, equipment, supplies, and personnel time, (2) change in the pattern of patient flow, (3) patient refusal or intolerance, (4) requirement of cleaning if reusable equipment is utilized, (5) insufficient availability of a power supply, (6) requirement to train personnel, (7) bypass of the holding area, (8) additional equipment maintenance requirement, and (9) inadequate knowledge of the value of prewarming [10].

Prewarming works by adding heat content to the periphery. This decreases the temperature gradient between core and periphery and thus decreases the heat transfer and redistribution hypothermia. Any method that can increase the peripheral temperature will reduce redistribution hypothermia. Any event that decreases peripheral temperature will increase redistribution. Thus, all reasonable efforts should be made to keep the periphery warm before induction of anesthesia. After application of forced-air warming, it will take time (usually 30 min) until an increase in core temperature occurs [41, 42]. This delay occurs because the periphery needs to be warmed before there is a significant effect on core temperature.

The efficacy of prewarming can be limited by sweating, thermal discomfort, and efficacy of the warming device. Sessler et al. found that 30 min of prewarming increased peripheral tissue heat content by more than the amount normally distributed during the first hour of anesthesia [43]. Since there are other and ongoing mechanisms of heat loss, prewarming more than 30 min will likely benefit many patients. However, if it is difficult to arrange for 30+ min of prewarming or the patient does not tolerate the longer durations, even 10–20 min of prewarming is effective in reducing hypothermia and shivering [44].

Because of redistribution hypothermia, ideally, every patient undergoing general or neuraxial anesthesia should be prewarmed [45, 46]. If the patient receives just a peripheral nerve block, there is little risk of hypothermia. Prewarming (and forced-air warming) should not be applied over ischemic limbs. Normally when there is heat transfer to an area of the body, blood circulation removes the heat from that area, thus decreasing the local temperature. If there is impaired blood flow, it is possible that the heat accumulation from prewarming or intraoperative forced-air warming could cause tissue damage. (In therapeutic hyperthermia, temperatures >42.0°C have been associated with tissue damage such as fat necrosis [47].) For similar reasons, forced-air warming over the lower extremities should be turned off during aortic cross-clamping. Also, in theory, there may be more risk of cell death from warming ischemic tissue because of the resulting increase in metabolic oxygen demand in combination with the impaired blood supply. It may be prudent to avoid prewarming when there is a contraindication to hyperthermia (e.g., risk of neurologic ischemia and pregnancy).

There is no data to guide the decision to use prewarming on patients who are hyperthermic preoperatively. Patients are hyperthermic because either (1) their cooling mechanisms have been overwhelmed as that which occurs in heat exhaustion or heatstroke (nonfebrile hyperthermia) or (2) they have an elevated temperature set point as occurs with many infections (febrile hyperthermia). The nonfebrile patients probably should be allowed to have their core temperature normalized and thus probably should not be prewarmed. It has been suggested that the febrile patients should be allowed to remain hyperthermic intraoperatively [48]. There is overwhelming evidence that fever is part of a coordinated defense system [49, 50]. The lines of evidence include evolutionary, correlative, antipyretic, and hyperthermia/hypothermia studies [49]. For example, infectious illnesses in animals are of longer duration, and mortality rates increase if the fever is treated [49]. Some of the enzymes in the immune system have a temperature optima in the febrile range. In addition, if the temperature of these patients decrease to below their elevated temperature set point and the set point does not change during the anesthetic, then these patients will behave postoperatively as though they are hypothermic (e.g., increasing metabolism and cardiac output, shivering), even if their temperature is >37.0°C. Thus, although unproven, there is reason to maintain the febrile hyperthermia intraoperatively. It is an unanswered question as to whether these patients should be prewarmed.

#### **2.3 Increase metabolic activity**

#### *2.3.1 Amino acid administration*

The preoperative administration of amino acids increases metabolic heat production and leads to the release of insulin and leptin resulting in a mean temperature increase of 0.46°C [51]. These hormones may also affect central thermoregulation. If amino acid infusion is started after hypothermia develops, rewarming is not augmented [52]. It is possible that the amino acid-induced increase in cardiopulmonary demands may be problematic in frail patients and those with reduced cardiopulmonary reserve. Since there is limited evidence, this technique is considered experimental.

#### *2.3.2 Fructose administration*

The preoperative administration of fructose increases metabolic heat production and affects central thermoregulation [53]. However, in patients with hereditary fructose intolerance (HFI), the infusion of fructose can lead to liver damage, kidney

**79**

*DOI: http://dx.doi.org/10.5772/intechopen.80830*

of any clinical data regarding these factors.

**2.4 Warming the environment**

will be greater [8].

from the patient.

events.

*Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults*

damage, convulsions, and death. HFI often goes undiagnosed. The prevalence of HFI is estimated at 1 in 20,000, similar to the incidence of malignant hyperthermia

As discussed above, anything that is practical and can be done to keep the patient warmer will likely result in the periphery remaining warmer and thus less redistribution. There is often a difference of opinion among various operating room personnel as to what temperature of the operating room should be. A cooler environment will increase the rate of heat loss from the patient. With the resultant decrease in peripheral heat content, the magnitude of redistribution hypothermia

There are five methods of heat loss (conduction, convection, radiation, evaporation, and loss via the airway). Radiation and convection losses are most important [54]. One of the major determinants of radiative heat loss is the temperature difference between the radiator (i.e., the patient) and the environment. A greater temperature difference will result in a greater heat loss. Another major determinant is the absorption/reflection properties of the environment. The author is unaware

Convection refers to heat transfer resulting from the bulk movement of a fluid (i.e., gas or liquid). A patient will transfer heat to warm the air immediately around him or herself. Convective airflow will move this warm air away from the patient and replace it with cooler ambient air. Thus, heat loss will continue to warm the newly adjacent cool air. The cooler the adjacent air, the greater the rate of heat loss

Surgeons generally prefer a cooler room because they are working, are under lights that may emit heat, may be under stress, are gowned, may be in physical contact with other personnel, and may also be wearing lead aprons. An uncomfortable surgeon may not work at his/her best and may drip perspiration into the surgical wound. With modern operating rooms where the air is replaced many times an hour, the temperature can be adjusted within minutes. Thus, a reasonable compromise would be to keep the operating room warm until the patient is prepped and draped and then cool the room for the benefit of the surgical team. Once the patient

Unfortunately, none of the abovementioned techniques fully solves the redistribution hypothermia problem. It is plausible that either reducing propofol dosages or combining techniques may provide additional thermal benefit. The following

1.Ketamine in analgesic doses is commonly used as part of a multimodal analgesia strategy. It is plausible that reducing the propofol dose by an analgesic dose of ketamine would reduce the magnitude of redistribution hypothermia. The induction dose of propofol (2.2 mg/kg) is similar in mg to the induction dose of ketamine (2 mg/kg). Reducing the propofol dose by 30 mg and replacing it

2.Kazama et al. found that patients can be induced with a reduced total dose of propofol and with less hypotension when diluted propofol was administered

is draped, convective losses are reduced except from the surgical wound.

**3. Candidate methods to reduce redistribution hypothermia**

techniques show promise but require formal investigation:

with 30 mg ketamine seems reasonable.

*DOI: http://dx.doi.org/10.5772/intechopen.80830 Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults*

damage, convulsions, and death. HFI often goes undiagnosed. The prevalence of HFI is estimated at 1 in 20,000, similar to the incidence of malignant hyperthermia events.

#### **2.4 Warming the environment**

*Autonomic Nervous System Monitoring - Heart Rate Variability*

Because of redistribution hypothermia, ideally, every patient undergoing general or neuraxial anesthesia should be prewarmed [45, 46]. If the patient receives just a peripheral nerve block, there is little risk of hypothermia. Prewarming (and forced-air warming) should not be applied over ischemic limbs. Normally when there is heat transfer to an area of the body, blood circulation removes the heat from that area, thus decreasing the local temperature. If there is impaired blood flow, it is possible that the heat accumulation from prewarming or intraoperative forced-air warming could cause tissue damage. (In therapeutic hyperthermia, temperatures >42.0°C have been associated with tissue damage such as fat necrosis [47].) For similar reasons, forced-air warming over the lower extremities should be turned off during aortic cross-clamping. Also, in theory, there may be more risk of cell death from warming ischemic tissue because of the resulting increase in metabolic oxygen demand in combination with the impaired blood supply. It may be prudent to avoid prewarming when there is a contra-

indication to hyperthermia (e.g., risk of neurologic ischemia and pregnancy).

There is no data to guide the decision to use prewarming on patients who are hyperthermic preoperatively. Patients are hyperthermic because either (1) their cooling mechanisms have been overwhelmed as that which occurs in heat exhaustion or heatstroke (nonfebrile hyperthermia) or (2) they have an elevated temperature set point as occurs with many infections (febrile hyperthermia). The nonfebrile patients probably should be allowed to have their core temperature normalized and thus probably should not be prewarmed. It has been suggested that the febrile patients should be allowed to remain hyperthermic intraoperatively [48]. There is overwhelming evidence that fever is part of a coordinated defense system [49, 50]. The lines of evidence include evolutionary, correlative, antipyretic, and hyperthermia/hypothermia studies [49]. For example, infectious illnesses in animals are of longer duration, and mortality rates increase if the fever is treated [49]. Some of the enzymes in the immune system have a temperature optima in the febrile range. In addition, if the temperature of these patients decrease to below their elevated temperature set point and the set point does not change during the anesthetic, then these patients will behave postoperatively as though they are hypothermic (e.g., increasing metabolism and cardiac output, shivering), even if their temperature is >37.0°C. Thus, although unproven, there is reason to maintain the febrile hyperthermia intraoperatively. It is an unanswered question as to whether these patients

The preoperative administration of amino acids increases metabolic heat production and leads to the release of insulin and leptin resulting in a mean temperature increase of 0.46°C [51]. These hormones may also affect central thermoregulation. If amino acid infusion is started after hypothermia develops, rewarming

is not augmented [52]. It is possible that the amino acid-induced increase in cardiopulmonary demands may be problematic in frail patients and those with reduced cardiopulmonary reserve. Since there is limited evidence, this technique is

The preoperative administration of fructose increases metabolic heat production

and affects central thermoregulation [53]. However, in patients with hereditary fructose intolerance (HFI), the infusion of fructose can lead to liver damage, kidney

**78**

should be prewarmed.

**2.3 Increase metabolic activity**

*2.3.1 Amino acid administration*

considered experimental.

*2.3.2 Fructose administration*

As discussed above, anything that is practical and can be done to keep the patient warmer will likely result in the periphery remaining warmer and thus less redistribution. There is often a difference of opinion among various operating room personnel as to what temperature of the operating room should be. A cooler environment will increase the rate of heat loss from the patient. With the resultant decrease in peripheral heat content, the magnitude of redistribution hypothermia will be greater [8].

There are five methods of heat loss (conduction, convection, radiation, evaporation, and loss via the airway). Radiation and convection losses are most important [54]. One of the major determinants of radiative heat loss is the temperature difference between the radiator (i.e., the patient) and the environment. A greater temperature difference will result in a greater heat loss. Another major determinant is the absorption/reflection properties of the environment. The author is unaware of any clinical data regarding these factors.

Convection refers to heat transfer resulting from the bulk movement of a fluid (i.e., gas or liquid). A patient will transfer heat to warm the air immediately around him or herself. Convective airflow will move this warm air away from the patient and replace it with cooler ambient air. Thus, heat loss will continue to warm the newly adjacent cool air. The cooler the adjacent air, the greater the rate of heat loss from the patient.

Surgeons generally prefer a cooler room because they are working, are under lights that may emit heat, may be under stress, are gowned, may be in physical contact with other personnel, and may also be wearing lead aprons. An uncomfortable surgeon may not work at his/her best and may drip perspiration into the surgical wound. With modern operating rooms where the air is replaced many times an hour, the temperature can be adjusted within minutes. Thus, a reasonable compromise would be to keep the operating room warm until the patient is prepped and draped and then cool the room for the benefit of the surgical team. Once the patient is draped, convective losses are reduced except from the surgical wound.

#### **3. Candidate methods to reduce redistribution hypothermia**

Unfortunately, none of the abovementioned techniques fully solves the redistribution hypothermia problem. It is plausible that either reducing propofol dosages or combining techniques may provide additional thermal benefit. The following techniques show promise but require formal investigation:


as an infusion [55]. It is plausible that, by using less propofol, there would be a lesser amount of redistribution hypothermia (and less hypotension).


#### **4. Summary**

At this time, prewarming is the most studied and likely the most effective method of reducing redistribution hypothermia, and improved outcomes have been documented. Unfortunately, it is not universally used. Given the priority of operating room expediency, either inhalation inductions or prophylactic administration of bolus phenylephrine are practical and can be used in virtually every anesthetizing location. Even though these techniques have been demonstrated to reduce redistribution hypothermia, and post-induction temperatures are similar to what one sees after prewarming and a propofol induction, we can only anticipate but not yet infer the same improved outcomes will accrue. Although a strong correlation of adverse outcomes and hypothermia has been documented in numerous studies, an outcome study is needed. Inhalation inductions or prophylactic administration of phenylephrine reduces redistribution hypothermia by reducing vasoconstriction; they do not add heat content. Prewarming reduces redistribution hypothermia by warming the periphery and adds heat content to the patient. Because the periphery needs to get warmed before forced-air warming increases the core temperature, it is likely that prewarmed patients will rewarm more rapidly, which is likely beneficial.

It is important to keep the operating room warm until the patient is prepped and draped. The temperature of a modern operating room can be decreased rapidly for the comfort of the operating room personnel. Putting a warm blanket on a patient as he/she enters a cold operating room does little to rewarm a patient. The skin temperature receptors have a disproportionate influence on the hypothalamus. The warm blanket may make the patient feel warmer, but the patient may still have lost significant heat content to the cool environment.

Besides from thermal benefits, financial benefits may accrue from reducing redistribution hypothermia. In the United States, the new Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) temperature target (35.5°C) may now be easier to achieve [56]. Avoidance of unpleasant side effects (e.g., shivering) may result in less patient dissatisfaction. Reducing hypothermia-associated complications will reduce costs.

**81**

**Author details**

Jonathan V. Roth1,2\*

Philadelphia, PA, USA

provided the original work is properly cited.

1 Albert Einstein Medical Center, Philadelphia, PA, USA

\*Address all correspondence to: jvroth1@aol.com

2 Sidney Kimmel Medical College - Thomas Jefferson University,

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

*Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults*

*DOI: http://dx.doi.org/10.5772/intechopen.80830*

*Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults DOI: http://dx.doi.org/10.5772/intechopen.80830*

#### **Author details**

*Autonomic Nervous System Monitoring - Heart Rate Variability*

potentially reduce redistribution hypothermia.

**4. Summary**

as an infusion [55]. It is plausible that, by using less propofol, there would be a

3.A blended propofol-inhalation induction would utilize less propofol and thus

4.Combining prewarming with any of the other techniques (e.g., prewarming and inhalation induction, prewarming and phenylephrine prior to propofol).

5.Combining prophylactic phenylephrine with inhalation inductions.

At this time, prewarming is the most studied and likely the most effective method of reducing redistribution hypothermia, and improved outcomes have been documented. Unfortunately, it is not universally used. Given the priority of operating room expediency, either inhalation inductions or prophylactic administration of bolus phenylephrine are practical and can be used in virtually every anesthetizing location. Even though these techniques have been demonstrated to reduce redistribution hypothermia, and post-induction temperatures are similar to what one sees after prewarming and a propofol induction, we can only anticipate but not yet infer the same improved outcomes will accrue. Although a strong correlation of adverse outcomes and hypothermia has been documented in numerous studies, an outcome study is needed. Inhalation inductions or prophylactic administration of phenylephrine reduces redistribution hypothermia by reducing vasoconstriction; they do not add heat content. Prewarming reduces redistribution hypothermia by warming the periphery and adds heat content to the patient. Because the periphery needs to get warmed before forced-air warming increases the core temperature, it is likely that

prewarmed patients will rewarm more rapidly, which is likely beneficial.

significant heat content to the cool environment.

tions will reduce costs.

It is important to keep the operating room warm until the patient is prepped and draped. The temperature of a modern operating room can be decreased rapidly for the comfort of the operating room personnel. Putting a warm blanket on a patient as he/she enters a cold operating room does little to rewarm a patient. The skin temperature receptors have a disproportionate influence on the hypothalamus. The warm blanket may make the patient feel warmer, but the patient may still have lost

Besides from thermal benefits, financial benefits may accrue from reducing redistribution hypothermia. In the United States, the new Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) temperature target (35.5°C) may now be easier to achieve [56]. Avoidance of unpleasant side effects (e.g., shivering) may result in less patient dissatisfaction. Reducing hypothermia-associated complica-

lesser amount of redistribution hypothermia (and less hypotension).

**80**

Jonathan V. Roth1,2\*

1 Albert Einstein Medical Center, Philadelphia, PA, USA

2 Sidney Kimmel Medical College - Thomas Jefferson University, Philadelphia, PA, USA

\*Address all correspondence to: jvroth1@aol.com

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

### **References**

[1] Sessler DI. Complications and treatment of mild hypothermia. Anesthesiology. 2001;**95**:531-543

[2] Stewart PA, Liang SS, Li QS, Huang ML, Bilgin AB, Kim D, et al. The impact of residual neuromuscular blockade, oversedation, and hypothermia on adverse respiratory events in a postanesthetic care unit: A prospective study of prevalence, predictors, and outcomes. Anesthesia and Analgesia. 2016;**123**(4):859-868

[3] Prielipp RC, Birnbach DJ. HCAinfections: Can the anesthesia provider be at fault? APSF Newsletter. 2018;**32**(2):64-65

[4] Winkler M, Akca O, Birkenberg B, Hetz H, Scheck T, Arkilic CF, et al. Aggressive warming reduces blood loss during hip arthroplasty. Anesthesia and Analgesia. 2000;**91**:978-984

[5] Ban KA, Minei JP, Laronga C, Harbrecht BG, Jensen EH, Fry DE, et al. American College of Surgeons and Surgical Infection Society: Surgical Infection Guidelines, 2016 update. Journal of the American College of Surgeons. 2017;**224**:59-74

[6] Berríos-Torres SI, Umscheid CA, Bratzler DW, Leas B, Stone EC, Kelz RR, et al. Centers for disease control and prevention guideline for the prevention of surgical site infection, 2017. JAMA Surgery. 2017;**152**(8):784-791

[7] Sun Z, Honar H, Sessler DI, Dalton JE, Yang D, Panjasawatwong K, et al. Intraoperative core temperature patterns, transfusion requirement, and hospital duration in patients warmed with forced air. Anesthesiology. 2015;**122**:276-285

[8] Brauer A. Influence of transportation to the operating room and preparation for surgery. In: Perioperative Temperature Management.

United Kingdom: Cambridge University Press; 2017. pp. 42-43. Chapter 6

[9] Brauer A. Physiology of thermoregulation. In: Perioperative Temperature Management. United Kingdom: Cambridge University Press; 2017. pp. 17-25. Chapter 3

[10] Brauer A. Prewarming. In: Perioperative Temperature Management. United Kingdom: Cambridge University Press; 2017. pp. 170-177. Chapter 32

[11] Ikeda T, Sessler DI, Kikura M, Kazama T, Ikeda K, Sato S. Less core hypothermia when anesthesia is induced with inhaled sevoflurane than with intravenous propofol. Anesthesia and Analgesia. 1999;**88**:921-924

[12] Park HP, Kang JM, Jeon YT, Choi IY, Oh YS, Hwang JW. Comparison of the effects of etomidate and propofol on redistribution hypothermia during general anesthesia. Korean Journal of Anesthesiology. 2006;**50**:S19-S24

[13] Ikeda T, Kazama T, Sessler DI, Toriyama S, Niwa K, Shimada C, et al. Induction of anesthesia with ketamine reduces the magnitude of redistribution hypothermia. Anesthesia and Analgesia. 2001;**93**:934-938

[14] Lundy JB, Slane ML, Frizzi JD. Acute adrenal insufficiency after a single dose of etomidate. Journal of Intensive Care Medicine. 2007;**22**(2):111-117

[15] Garfeld JM, Garfield FB, Stone JG, Hopkins D, Johns LA. A comparison of psychologic responses to ketamine and thiopental-nitroushalothane anesthesia. Anesthesiology. 1972;**36**:329-338

[16] Ikeda T, Ozaki M, Sessler DI, Kazama T, Ikeda K, Sato S. Intraoperative phenylephrine infusion decreases the magnitude of

**83**

*Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults*

[25] Thomas DV. Propofol supports bacterial growth. British Journal of

[26] Cole DC, Baslanti TO, Gravenstein NL, Gravenstein N: Leaving more than your fingerprint on the intravenous line: A prospective study on propofol

Anaesthesia. 1991;**66**:274

and implications of stopcock contamination. Anesthesia and Analgesia. 2015;**120**(4):861-867

[27] Ozaki M, Sessler DI, Suzuki H, Ozaki K, Tsunoda C, Atarashi K. Nitrous

oxide decreases the threshold for

[28] Myles PS, Leslie K, Chan MTV, Forbes A, Peyton PJ, Pasch MJ, et al. ANZCA Trials Group for the ENIGMA-II Investigators: The safety of addition of nitrous oxide to general anaesthesia in at-risk patients having major noncardiac surgery (ENIGMA-II): A randomized, single-blind trial. Lancet.

1995;**80**(6):1212-1216

2014;**384**:1446-1454

[29] Turan A, Mascha EJ, You J, Kurz A, Shiba A, Saager L, et al. The association between nitrous oxide and postoperative mortality and morbidity after noncardiac surgery. Anesthesia and Analgesia. 2013;**116**:1026-1033

[30] Fleisher LA. Value of sequels. Is it safe to include nitrous oxide in your anesthetic. Anesthesiology.

[31] Leslie K, Myles PS, Kasza J, Forbes A, Peyton PJ, Chan MTV, et al. Nitrous oxide and serious long-term morbidity and mortality in the evaluation of nitrous oxide in the gas mixture for anaesthesia (ENIGMA)-II trail. Anesthesiology. 2015;**123**(6):1267-1280

[32] Chan MT, Peyton PJ, Myles PS, et al. Chronic postsurgical pain in the evaluation of nitrous oxide in the gas

2015;**123**(6):1229-1230

vasoconstriction less than sevoflurane or isoflurance. Anesthesia and Analgesia.

*DOI: http://dx.doi.org/10.5772/intechopen.80830*

redistribution hypothermia. Anesthesia

[17] Roth JV, Braitman LE. Induction

redistribution hypothermia. Abstract Presented at the American Society of Anesthesiologists Annual Meeting;

[18] Roth JV, Braitman LE. Induction

redistribution hypothermia. Abstract

[19] Vaughan MS, Vaughan RW, Cook RC. Postoperative hypothermia in adults: Relationship of age, anesthesia, and shivering to rewarming. Anesthesia

and Analgesia. 1999;**89**(2):

techniques that can reduce

techniques that can reduce

Meeting, #1135; May 2017

Presented at the International Anesthesia Research Society Annual

and Analgesia. 1981;**60**:746-751

[20] Kurz A, Plattner O, Sessler DI, Huemer G, Redi G, Lackner F. The threshold for thermoregulatory vasoconstriction during nitrous oxide/ isoflurane anesthesia is lower in elderly than in young patients. Anesthesiology.

[21] Sessler DI. Temperature monitoring and perioperative thermoregulation. Anesthesiology. 2008;**109**(2):318-338

propofol. British Journal of Anaesthesia.

TJ. Induction of anesthesia and tracheal intubation with sevoflurane in adults. Anesthesiology. 1996;**85**:536-543

[24] Van den Berg AA, Chitty DA, Jones RD, Sohel MS, Shahen A. Intravenous or inhaled induction of anesthesia in adults? An audit of preoperative patient preferences. Anesthesia & Analgesia.

[22] Thwaites A, Edmends S, Smith I. Inhalation induction with sevoflurane:

A double-blind comparison with

[23] Muzi M, Robinson BJ, Ebert

October 23, 2016

1993;**79**:465-469

1997;**78**(4):356-361

2005;**100**(5):1422-1424

462-465

*Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults DOI: http://dx.doi.org/10.5772/intechopen.80830*

redistribution hypothermia. Anesthesia and Analgesia. 1999;**89**(2): 462-465

[17] Roth JV, Braitman LE. Induction techniques that can reduce redistribution hypothermia. Abstract Presented at the American Society of Anesthesiologists Annual Meeting; October 23, 2016

[18] Roth JV, Braitman LE. Induction techniques that can reduce redistribution hypothermia. Abstract Presented at the International Anesthesia Research Society Annual Meeting, #1135; May 2017

[19] Vaughan MS, Vaughan RW, Cook RC. Postoperative hypothermia in adults: Relationship of age, anesthesia, and shivering to rewarming. Anesthesia and Analgesia. 1981;**60**:746-751

[20] Kurz A, Plattner O, Sessler DI, Huemer G, Redi G, Lackner F. The threshold for thermoregulatory vasoconstriction during nitrous oxide/ isoflurane anesthesia is lower in elderly than in young patients. Anesthesiology. 1993;**79**:465-469

[21] Sessler DI. Temperature monitoring and perioperative thermoregulation. Anesthesiology. 2008;**109**(2):318-338

[22] Thwaites A, Edmends S, Smith I. Inhalation induction with sevoflurane: A double-blind comparison with propofol. British Journal of Anaesthesia. 1997;**78**(4):356-361

[23] Muzi M, Robinson BJ, Ebert TJ. Induction of anesthesia and tracheal intubation with sevoflurane in adults. Anesthesiology. 1996;**85**:536-543

[24] Van den Berg AA, Chitty DA, Jones RD, Sohel MS, Shahen A. Intravenous or inhaled induction of anesthesia in adults? An audit of preoperative patient preferences. Anesthesia & Analgesia. 2005;**100**(5):1422-1424

[25] Thomas DV. Propofol supports bacterial growth. British Journal of Anaesthesia. 1991;**66**:274

[26] Cole DC, Baslanti TO, Gravenstein NL, Gravenstein N: Leaving more than your fingerprint on the intravenous line: A prospective study on propofol and implications of stopcock contamination. Anesthesia and Analgesia. 2015;**120**(4):861-867

[27] Ozaki M, Sessler DI, Suzuki H, Ozaki K, Tsunoda C, Atarashi K. Nitrous oxide decreases the threshold for vasoconstriction less than sevoflurane or isoflurance. Anesthesia and Analgesia. 1995;**80**(6):1212-1216

[28] Myles PS, Leslie K, Chan MTV, Forbes A, Peyton PJ, Pasch MJ, et al. ANZCA Trials Group for the ENIGMA-II Investigators: The safety of addition of nitrous oxide to general anaesthesia in at-risk patients having major noncardiac surgery (ENIGMA-II): A randomized, single-blind trial. Lancet. 2014;**384**:1446-1454

[29] Turan A, Mascha EJ, You J, Kurz A, Shiba A, Saager L, et al. The association between nitrous oxide and postoperative mortality and morbidity after noncardiac surgery. Anesthesia and Analgesia. 2013;**116**:1026-1033

[30] Fleisher LA. Value of sequels. Is it safe to include nitrous oxide in your anesthetic. Anesthesiology. 2015;**123**(6):1229-1230

[31] Leslie K, Myles PS, Kasza J, Forbes A, Peyton PJ, Chan MTV, et al. Nitrous oxide and serious long-term morbidity and mortality in the evaluation of nitrous oxide in the gas mixture for anaesthesia (ENIGMA)-II trail. Anesthesiology. 2015;**123**(6):1267-1280

[32] Chan MT, Peyton PJ, Myles PS, et al. Chronic postsurgical pain in the evaluation of nitrous oxide in the gas

**82**

*Autonomic Nervous System Monitoring - Heart Rate Variability*

United Kingdom: Cambridge University

Press; 2017. pp. 42-43. Chapter 6

thermoregulation. In: Perioperative

United Kingdom: Cambridge University

[9] Brauer A. Physiology of

Temperature Management.

[10] Brauer A. Prewarming. In: Perioperative Temperature Management. United Kingdom: Cambridge University Press; 2017.

pp. 170-177. Chapter 32

Analgesia. 1999;**88**:921-924

Press; 2017. pp. 17-25. Chapter 3

[11] Ikeda T, Sessler DI, Kikura M, Kazama T, Ikeda K, Sato S. Less core hypothermia when anesthesia is induced with inhaled sevoflurane than with intravenous propofol. Anesthesia and

[12] Park HP, Kang JM, Jeon YT, Choi IY, Oh YS, Hwang JW. Comparison of the effects of etomidate and propofol on redistribution hypothermia during general anesthesia. Korean Journal of Anesthesiology. 2006;**50**:S19-S24

[13] Ikeda T, Kazama T, Sessler DI, Toriyama S, Niwa K, Shimada C, et al. Induction of anesthesia with ketamine reduces the magnitude of redistribution hypothermia. Anesthesia and Analgesia.

[14] Lundy JB, Slane ML, Frizzi JD. Acute adrenal insufficiency after a single dose of etomidate. Journal of Intensive Care Medicine. 2007;**22**(2):111-117

[15] Garfeld JM, Garfield FB, Stone JG, Hopkins D, Johns LA. A comparison of psychologic responses to ketamine and thiopental-nitroushalothane anesthesia. Anesthesiology.

[16] Ikeda T, Ozaki M, Sessler DI, Kazama T, Ikeda K, Sato S. Intraoperative phenylephrine infusion decreases the magnitude of

2001;**93**:934-938

1972;**36**:329-338

[1] Sessler DI. Complications and treatment of mild hypothermia. Anesthesiology. 2001;**95**:531-543

**References**

2016;**123**(4):859-868

2018;**32**(2):64-65

[2] Stewart PA, Liang SS, Li QS, Huang ML, Bilgin AB, Kim D, et al. The impact of residual neuromuscular blockade, oversedation, and hypothermia on adverse respiratory events in a postanesthetic care unit: A prospective study of prevalence, predictors, and outcomes. Anesthesia and Analgesia.

[3] Prielipp RC, Birnbach DJ. HCAinfections: Can the anesthesia

[4] Winkler M, Akca O, Birkenberg B, Hetz H, Scheck T, Arkilic CF, et al. Aggressive warming reduces blood loss during hip arthroplasty. Anesthesia and

Analgesia. 2000;**91**:978-984

Surgeons. 2017;**224**:59-74

Surgery. 2017;**152**(8):784-791

for surgery. In: Perioperative Temperature Management.

[5] Ban KA, Minei JP, Laronga C, Harbrecht BG, Jensen EH, Fry DE, et al. American College of Surgeons and Surgical Infection Society: Surgical Infection Guidelines, 2016 update. Journal of the American College of

[6] Berríos-Torres SI, Umscheid CA, Bratzler DW, Leas B, Stone EC, Kelz RR, et al. Centers for disease control and prevention guideline for the prevention of surgical site infection, 2017. JAMA

[7] Sun Z, Honar H, Sessler DI, Dalton JE, Yang D, Panjasawatwong K, et al. Intraoperative core temperature patterns, transfusion requirement, and hospital duration in patients warmed with forced air. Anesthesiology. 2015;**122**:276-285

[8] Brauer A. Influence of transportation to the operating room and preparation

provider be at fault? APSF Newsletter.

mixture for anaesthesia (EnNIGMA)-II trial. British Journal of Anaesthesia. 2016;**117**:801-811

[33] Quinones S. Dreamland: The True Tale of America's Opiate Epidemic. New York, NY: Bloomsbury Press; 2015

[34] Roth JV. Chronic pain and the opioid epidemic. Are we ignoring the potential benefits of nitrous oxide? Anesthesia & Analgesia. 2018;**126**(4):1423-1424

[35] Just B, Trevien V, Lelva E, Lienhart A. Prevention of intraoperative hypothermia by preoperative skinsurface warming. Anesthesiology. 1993;**79**:214-218

[36] Andrzejowski J, Hoyle J, eapen G, Turnbull D. Effect of prewarming on post-induction core temperature and the incidence of inadvertent perioperative hypothermia in patients undergoing general anaesthesia. British Journal of Anaesthesia. 2008;**101**:627-631

[37] Bock M, Muller J, Bach A, Bohrer H, Martin E, Motsch J. Effects of preinduction and intraoperative warming during major laparotomy. British Journal of Anaesthesia. 1998;**80**:159-163

[38] Camus Y, Delva E, Sessler DI, Lienhart A. Pre-induction skin-surface warming minimizes intraoperative core hypothermia. Journal of Clinical Anesthesia. 1995;**7**:384-388

[39] Hynson JM, Sessler DI, Moayeri A, McGuire J, Schroeder BS. The effects of pre-induction warming on temperature and blood pressure during propofol-nitrous oxide anesthesia. Anesthesiology. 1993;**79**:219-228

[40] Brauer A, Russo M, Nickel EA, Bauer M, Russo SG. Anwendungsrealitat des peripoperativen Warmemanagements in Deutschland. Ergebnisse einer Online-Umfrage. Anästhesiologie und Intensivmedizin. 2015;**56**:287-297

[41] Negishi C, Hasegawa K, Mukai S, Nakagawa F, Ozaki M, Sessler DI. Resistive heating and forcedair warming are comparatively effective. Anesthesia and Analgesia. 2003;**96**:1683-1687

[42] Kimberger O, Held C, Stadelmann K, Mayer N, Hunkeler C, Sessler DI, et al. Resistive polymer versus forced-air warming: Comparable heat transfer and core rewarming rates in volunteers. Anesthesia and Analgesia. 2008;**107**:1621-1626

[43] Sessler DI, Schroeder BA, Merrifield B, Matsukawa T, Cheng C. Optimal duration and temperature of prewarming. Anesthesiology. 1995;**82**:674-681

[44] Horn EP, Bein B, Bohm R, Steinfath M, Sahili N, Hocker J. The effect of short time periods of preoperative warming in the prevention of perioperative hypothermia. Anaesthesia. 2012;**67**:612-617

[45] Matsukawa T, Sessler DI, Sessler AM, Schroeder BA, Ozaki M, Kurz A, et al. Heat flow and distribution during induction of general anesthesia. Anesthesiology. 1995;**82**:662-673

[46] Matsukawa T, Sessler DI, Christensen R, Ozaki M, Schroeder M. Heat flow and distribution during epidural anesthesia. Anesthesiology. 1995;**83**:961-967

[47] Mackowiak PA, Boulant JA. Fever's glass ceiling. Clinical Infectious Diseases. 1996;**22**:525-536

[48] Roth JV. Some unanswered questions about temperature management. Anesthesia & Analgesia. 2009;**109**(5):1695-1699

[49] Kluger MJ, Kozak W, Conn CA, Leon LR, Soszynski D. The adaptive value of fever. Infectious Disease Clinics of North America. 1996;**10**:1-20

**85**

*Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults*

*DOI: http://dx.doi.org/10.5772/intechopen.80830*

[50] Mackowiak PA. Fever: Blessing or curse? A unifying hypothesis. Annals of Internal Medicine. 1994;**120**:1037-1040

[51] Aoki Y, Aoshima Y, Atsumi K, Kaminaka R, Nakau R, Yanagida K, et al. Perioperative amino acid infusion for preventing hypothermia and improving clinical outcomes during surgery unger general anesthesia: A systematic review and meta-analysis. Anesthesia and Analgesia. 2017;**125**:793-802

[52] Inoue S, Shinjo T, Kawaguchi M, Nakajima Y, Furuya H. Amino acid infusions started after development of intraoperative core hypothermia do not affect rewarming but reduce the incidence of postoperative shivering during major abdominal surgery: A randomized trial. Journal of Anesthesia.

[53] Mizobe T, Nakajima Y, Ueno H, Sessler DI. Fructose administration increases intraoperative core temperature by augmenting both metabolic rate and the vasoconstriction

threshold. Anesthesiology. 2006;**104**:1124-1130

pp. 26-32. Chapter 4

2000;**92**:1017-1028

November 4, 2016

[54] Brauer A. Physiology of Heat Gain and Heat Loss. United Kingdom: Cambridge University Press; 2017.

[55] Kazama T, Ikeda K, Morita K, Kikura M, Ikeda T, Kurita T, et al. Investigation of effective anesthesia induction doses using a wide range of infusion rates with undiluted and diluted propofol. Anesthesiology.

[56] MIPS Standard #424. The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA). Centers for Medicare and Medicaid Services. Federal Register;

2011;**25**:850-854

*Techniques to Reduce the Magnitude and Duration of Redistribution Hypothermia in Adults DOI: http://dx.doi.org/10.5772/intechopen.80830*

[50] Mackowiak PA. Fever: Blessing or curse? A unifying hypothesis. Annals of Internal Medicine. 1994;**120**:1037-1040

*Autonomic Nervous System Monitoring - Heart Rate Variability*

[41] Negishi C, Hasegawa K, Mukai S, Nakagawa F, Ozaki M, Sessler DI. Resistive heating and forcedair warming are comparatively effective. Anesthesia and Analgesia.

[42] Kimberger O, Held C, Stadelmann K, Mayer N, Hunkeler C, Sessler DI, et al. Resistive polymer versus forced-air warming: Comparable heat transfer and core rewarming rates in volunteers. Anesthesia and Analgesia.

2003;**96**:1683-1687

2008;**107**:1621-1626

1995;**82**:674-681

[43] Sessler DI, Schroeder BA, Merrifield B, Matsukawa T, Cheng C. Optimal duration and temperature of prewarming. Anesthesiology.

[44] Horn EP, Bein B, Bohm R, Steinfath M, Sahili N, Hocker J. The effect of short time periods of preoperative warming in the prevention of perioperative hypothermia. Anaesthesia. 2012;**67**:612-617

[45] Matsukawa T, Sessler DI, Sessler AM, Schroeder BA, Ozaki M, Kurz A, et al. Heat flow and distribution during induction of general anesthesia. Anesthesiology. 1995;**82**:662-673

[47] Mackowiak PA, Boulant JA. Fever's

management. Anesthesia & Analgesia.

[49] Kluger MJ, Kozak W, Conn CA, Leon LR, Soszynski D. The adaptive value of fever. Infectious Disease Clinics

of North America. 1996;**10**:1-20

glass ceiling. Clinical Infectious Diseases. 1996;**22**:525-536

[48] Roth JV. Some unanswered questions about temperature

2009;**109**(5):1695-1699

[46] Matsukawa T, Sessler DI, Christensen R, Ozaki M, Schroeder M. Heat flow and distribution during epidural anesthesia. Anesthesiology.

1995;**83**:961-967

mixture for anaesthesia (EnNIGMA)-II trial. British Journal of Anaesthesia.

[33] Quinones S. Dreamland: The True Tale of America's Opiate Epidemic. New York, NY: Bloomsbury Press;

[34] Roth JV. Chronic pain and the opioid epidemic. Are we ignoring the potential benefits of nitrous oxide? Anesthesia & Analgesia. 2018;**126**(4):1423-1424

[35] Just B, Trevien V, Lelva E, Lienhart

[36] Andrzejowski J, Hoyle J, eapen G, Turnbull D. Effect of prewarming on post-induction core temperature and the incidence of inadvertent perioperative hypothermia in patients undergoing general anaesthesia. British Journal of

[37] Bock M, Muller J, Bach A, Bohrer H,

A. Prevention of intraoperative hypothermia by preoperative skinsurface warming. Anesthesiology.

Anaesthesia. 2008;**101**:627-631

Martin E, Motsch J. Effects of preinduction and intraoperative warming during major laparotomy. British Journal of Anaesthesia.

[38] Camus Y, Delva E, Sessler DI, Lienhart A. Pre-induction skin-surface warming minimizes intraoperative core hypothermia. Journal of Clinical

[39] Hynson JM, Sessler DI, Moayeri A,

[40] Brauer A, Russo M, Nickel EA, Bauer M, Russo SG. Anwendungsrealitat des peripoperativen Warmemanagements in Deutschland. Ergebnisse einer Online-Umfrage. Anästhesiologie und Intensivmedizin. 2015;**56**:287-297

Anesthesia. 1995;**7**:384-388

McGuire J, Schroeder BS. The effects of pre-induction warming on temperature and blood pressure during propofol-nitrous oxide anesthesia. Anesthesiology. 1993;**79**:219-228

2016;**117**:801-811

1993;**79**:214-218

1998;**80**:159-163

2015

**84**

[51] Aoki Y, Aoshima Y, Atsumi K, Kaminaka R, Nakau R, Yanagida K, et al. Perioperative amino acid infusion for preventing hypothermia and improving clinical outcomes during surgery unger general anesthesia: A systematic review and meta-analysis. Anesthesia and Analgesia. 2017;**125**:793-802

[52] Inoue S, Shinjo T, Kawaguchi M, Nakajima Y, Furuya H. Amino acid infusions started after development of intraoperative core hypothermia do not affect rewarming but reduce the incidence of postoperative shivering during major abdominal surgery: A randomized trial. Journal of Anesthesia. 2011;**25**:850-854

[53] Mizobe T, Nakajima Y, Ueno H, Sessler DI. Fructose administration increases intraoperative core temperature by augmenting both metabolic rate and the vasoconstriction threshold. Anesthesiology. 2006;**104**:1124-1130

[54] Brauer A. Physiology of Heat Gain and Heat Loss. United Kingdom: Cambridge University Press; 2017. pp. 26-32. Chapter 4

[55] Kazama T, Ikeda K, Morita K, Kikura M, Ikeda T, Kurita T, et al. Investigation of effective anesthesia induction doses using a wide range of infusion rates with undiluted and diluted propofol. Anesthesiology. 2000;**92**:1017-1028

[56] MIPS Standard #424. The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA). Centers for Medicare and Medicaid Services. Federal Register; November 4, 2016

**87**

Section 3

Special Focus
