**1. Introduction**

The urgency of the work is associated with pandemic COVID-19 [1, 2]. Due to a large-scale pandemic, the SARSCoV-2 virus has become the focus of researchers around the world [3]. To date, the pathogenetic mechanisms of development of COVID-19 are insufficiently studied [4]. Changes in the mental status of patients complicate the course of the disease [5–7]. The search for markers of complex pathological processes that occur in COVID-19 to improve methods of diagnosis,

treatment, control of long-term results of this dangerous disease, which course largely depends on the adaptive capacity of the body is continued [3].

The level of adaptability of the body is one of the important health criteria [8]. The circulatory system with its neurohumoral control apparatus and self-regulation is a universal indicator of the adaptive activity of the whole body [9].

An available method for assessing global hemodynamic processes is blood pressure (BP) monitoring [8–16]. The response of blood vessels to compression indicates: the state of coordination between local self-regulatory mechanisms and the central, neurohumoral regulation of the cardiovascular system (CVS) [13–16]; the level of the autonomic nervous system (ANS) [11, 12]; functional ability of the heart, reflex reaction of CVS [14, 15]; the state of the peripheral vascular bed (tone, elasticity, resilience, patency) [15, 16], the activity of the mechanisms of the urgent reaction to compression (baroreceptors, chemoreceptors, ischemia reflex), etc [14–16].

Various invasive and non-invasive devices are used to record the arterial signal [17–22]. The introduction of information technology for its analysis makes it possible to significantly expand the informativeness of blood pressure measurement results [23–28]. The methods used in the mathematical analysis of heart rate variability (HRV) are promising for assessing arterial pulsations [19, 20, 22].

HRV is an integral indicator of the functional state of the body, reflecting the activity of the main physiological systems. It makes it possible to obtain information from 4 levels of CVS regulation activity: peripheral, autonomic, hypothalamic– pituitary, central nervous system [8, 9, 24–26]. A minimum number of levels of the system is involved with optimal regulation to ensure the adaptation of the body. The inclusion of higher levels of regulation is due to the inability of the previous ones to cope with their functions and, if necessary, to coordinate the activities of several subsystems. The higher the body's adaptive capacity, the more reliable the protection, the lower the risk of disease [8, 9, 12, 13, 28–30].

How do adaptation processes occur in patients with COVID-19? To date, the pathogenetic mechanisms of development of COVID-19 are insufficiently studied [4]. Our study is devoted to the determination of the adaptive capacity of the body and the mechanisms of their violation in the severe course of COVID-19 using arterial oscillography AOG.

## **2. Methods**

The studies are based on the results of temporal, spectral, correlation analysis of AOG, registered during the measurement of BP. 67 patients with severe COVID-19 who were treated at the Ternopil Regional Phthisio-Pulmonology Center (main group) were examined. The control group (573 patients) included students of I. Horbachevsky Ternopil National Medical University and Volodymyr Hnatiuk Ternopil National Pedagogical University, as well as 28 patients who were treated in a Closed Department of Ternopil Regional Psychoneurological Hospital.

The main group included 67 patients with COVID-19, who were prescribed intensive care at the Ternopil Regional Phthisio-Pulmonology Center. Among them – 34 (50.7%) men and 33 (49.3%) women. By age – up to 20 years – 1 (1.5%), 21–40 – 19 (28.4%), 41–46 – 29 (43.3%), over 60 years – 18 (26.8%). The most typical complaints of patients on admission: fever and cough (100%), shortness of breath (79.1%), general weakness (71.6%), sore throat (47.8%), loss of smell (38.8%) and taste (23.9%), chest pain (31.3%), hyperhidrosis (28.4%). Complaints of depression or euphoria, insomnia, mood swings with aggression, sometimes

#### *Aplication Arterial Oscilography to Study the Adaptive Capacity of Subject with COVID-19… DOI: http://dx.doi.org/10.5772/intechopen.98570*

psychomotor agitation were observed in 26.8% of patients. The study was conducted from March to September 2020.

The diagnosis was made on the basis of anamnesis, complaints, contact with other patients, laboratory tests, in particular the detection of genetic material (RNA) SARS-CoV-2 by polymerase chain reaction. A positive result of the polymerase chain reaction was observed in 57 (85.1%). Saturation is less than 95% – in 26 (38.8%), changes in the lungs on the radiograph – in 65 (97.0%) patients. Among laboratory indicators lymphopenia (34.3%) and accelerated ESR (41.8%) were noted. Nonspecific flora was found in the sputum of 19 people (28.4%). Among comorbidities, cardiovascular diseaes (46.3%). After performed treatment, patients in satisfactory condition were discharged to continue outpatient treatment.

AOG was recorded during BP measurement when patient's admission and during treatment. 282 AOGs were registered. The article presents an analysis of 68 of them (registered on admission).

The control group included 548 people aged 18–22 without health complaints (CG-1), selected by random, voluntarily, by oral consent. CG-2 included 28 patients treated in a closed department of a psychoneurological hospital. AOG was recorded in them during the BP measurement in the process of treatment. The research results were used for comparative assessment of the adaptive capacity of the cardiovascular, autonomic, central nervous systems of the experimental and control groups.

CG-1 consitsed of 3 groups. CG 1-a – the largest one, included 548 people aged 18–22 without health complaints. AOG was registered in them at rest. The obtained results were used for their general assessment as a standard of indicators of AOG of healthy and comparison with patients with COVID -19 [19].

CG 1-b included 54 persons of the control group, electrocardiogram (ECG) synchronously with AOG was recorded, who were also subjected to temporal and spectral analysis [9, 10, 20, 21]. The obtained results were used for comparative analysis of the correspondence of individual indicators of HRV electrocardiographic signal [8–10, 25] and AOG [19–22].

CG 1-c included 68 members of the control group (45 males and 23 females) aged 18–22 without health complaints. AOG was recorded at rest, immediately after the Ruffier test (30 squats in 45 second, [9, 27] and after 2 minutes of rest). Used to study the dynamics of AOG under the influence of stress (physiological) factors, assessment of adaptation mechanisms at the same time and comparison with indicators of patients with severe COVID-19.

CG-2 included 28 patients (aged 32–65) who were treated at the Ternopil Regional Clinical Psychoneurological Hospital (TRCPH), in a Closed Department for patients with mental disorders. The choice for monitoring CG-2 is due to the appearance in the information sources of indications for the presence of patients with COVID-19 mental disorders in the form of depression, euphoria, insomnia, mood swings with aggression, sometimes psychomotor agitation on the background of severe hypoxia [3, 5–7]. Complaints and indicators of temporal and correlation analysis of AOG in patients of the closed department were closest to AOG in patients with COVID-19 [21].

The CG-2 examination program included clinical and psychological studies (clinical and psychological interview, collection of psychological history). The main range of diagnoses: paranoid schizophrenia, bipolar disorder and severe depressive disorders with psychotic inclusions, requiring systematic and long-term, usually lifelong use of antipsychotropic drugs.

*Arterial oscillography.* The information technologies of temporal, spectral, correlation analysis of AOG registered at BP measurement (in shoulder compression

growth) by means of the electronic tonometer VAT 41–2, ICS Techno [19–21] are developed in the work. For their analysis, the methods, indicators, terminology used in the study and evaluation of the results of mathematical analysis of HRV electrocardiographic signal were used [8, 9, 14, 24–34]. We analyzed both the indicators obtained during the compression of the shoulder, and in its individual (five) periods [19–22] to study and evaluate the process of adaptation of the body to shoulder compression.

*Temporal analysis* of oscillograms was performed by statistical analysis of the variability of the pulsation duration [19–21]. The values of indicators were studied: SDSD, RMSSD, pNN50, Mo, AMo, BP; IVR, VPR, IN, HVR index. Temporal analysis makes it possible to assess the state of the cardiovascular, autonomic nervous systems and the level of centralization management of their activities [8, 9, 14, 24–34].

Spectral (frequency) analysis of oscillograms. Realization of rhythmic activity of heart is possible only in certain phase relations between oscillating brain and cardiac processes. The control system of these rhythms is functionally and morphologically part of a single adaptive vertical, ensuring the adaptation of the body to conditions of external and internal environment [8, 9, 14, 24–34].

*Spectral analysis* of AOG was performed by determining the power of the spectrum in the range from 0 to 0.4 Hz: HF – high frequencies, LF, VLF, ULF (low, very low and ultra-low frequencies). Fast, slow, very slow and ultra-slow regulation is controlled by all links (parasympathetic, sympathetic, humoral, thermoregulatory, etc.). The influence of PSL is greater in fast, sympathetic - in slow and very slow, and humoral - in very slow and ultra-slow regulation [8, 9, 14, 24–34]. Due to indicators in the ranges: 0–4 Hz (Delta), 4–8 Hz (Theta), 8–13 Hz (Alpha), 13–25 Hz, 25 Hz and more Hz (Beta) were able to determine the level of brain activity. For this purpose, Fourier and Hilbert-Huang transform methods were used, which reflect the general and instantaneous adaptive response to shoulder compression [24, 34].

*Correlation analysis*. In the correlation analysis of the arterial oscillogram, the values of the Pearson correlation coefficient from 0.9 to 1 and − 0.9 to −1 were taken into account. The selected correlation values were subject to Cluster analysis (k-means clustering) [35–38], where the calculated correlation values were grouped separately in the middle of one experiment in 12 clusters.

#### **2.1 Statistical methods**

Statistical analysis of the data was conducted using the software package "OscEcgReoPuls", which was developed in "Matlab". The statistical significance of differences between the arithmetic average and relative values was estimated by Student's t-test (t) for the normally distributed data set. For samples that differed from the normal distribution, the Wilcoxon method was used. During the comparison of all variants of indicators within the limits of one experiment, we conducted a liaison analysis of the correlation coefficient (r) by the Pearson method [37, 38]. Statistical calculation was additionally processed in Statistica 10 software.

The urgency of the work is associated with the pandemic COVID-19. The obtained results will help doctors to pay attention to possible variants of mechanisms of pathogenetic processes at COVID-19, to plan preventive, diagnostic, medical, rehabilitation process [4].

The obtained results will help doctors to pay attention to possible variants of mechanisms of development of pathogenetic processes at COVID-19, to plan preventive, diagnostic, medical, rehabilitation process.

*Aplication Arterial Oscilography to Study the Adaptive Capacity of Subject with COVID-19… DOI: http://dx.doi.org/10.5772/intechopen.98570*
