**1.1 Data and methods**

This chapter models the agitation-sedation profiles of 36 patients collected at the Christchurch Hospital, Christchurch School of Medicine and Health Sciences, NZ. Two measures were recorded for each patient: (1) the nurses' ratings/scores of a patient's agitation level, and (2) an automated sedation dose (see **Figure 1**). Infusion data were recorded using an electronic drug infusion device for all admitted ICU patients during a nine-month observation period and required more than 24 hours of sedation. Infusion data containing less than 48 hours of continuous data, or data from patients whose sedation requirements were extreme, such as those with severe head injuries, were excluded [9, 10].

A total of 36 ICU patients met these requirements and were enrolled in the study. Classification of patients into poor and good trackers, based on the Wavelet Probability Bands (WPB), is given in **Table 1**. The so-called good tracker delineates the scenario where the nurse's rating scores remains within the (time-based) 90% coverage of wavelet probability band (WPB) based on the simulated dose profiles [10, 11]. Poor tracking delineates the scenario where the nurses' rating scores remain outside the (time based) 90% coverage of wavelet probability band (WPB) for a significant portion of time based on the simulated dose profiles [11].

By way of illustration, we carefully examine four patients from the pool of 36 patients. **Tables 2** and **3** summarise each of these 4 patients' WPB tracker status, time to first, second and third violation outside the WPB bands, their total number of violations over ICU stay, and patient's time in ICU, along with their specific WPB% value. Display of their line profiles of *nurses' rating* of A-S in relation to drug infusion *dose* over time, for each of the 4 patients (P8, P27, P18, P28) are given in **Figures 2**–**4**.

#### **Figure 1.**

*Diagram of the feedback loop employing nursing staff's feedback of subjectively assessed patient agitation through the infusion controller (diagram is sourced from Chase et al.) [12, 14].*


*Copula Modelling of Agitation-Sedation (A-S) in ICU: Threshold Analysis of Nurses'… DOI: http://dx.doi.org/10.5772/intechopen.105753*

**Table 1.** *Patient numbers of the poor trackers according to the criteria of 4 studies, developed earlier in [11].*


#### **Table 2.**

*Time to the patient-specific, 1st violation denoted by V1, second violation V2 and third violation V3, total number of violations, total ICU time and WPB% values.*


#### **Table 3.**

*Time to the patient-specific, 1st violation V1, second violation V2, and third violation V3, total number of violations, total ICU time and WPB% values.*

Note that a violation event occurs when the nurses observed agitation score or rating is outside either the lower or upper limits of the 90%WPB bands associated with the patient's automated infusion dose trajectory over time in ICU.

**Figure 2.** *Line plot of nurses' rating of patient agitation and the automated sedation dose for patient 8 (WPB-based good tracker).*

**Figure 3.**

*Line plot of nurses' rating of patient agitation and the automated sedation dose for patient 27 (WPB-based poor tracker).*

**Figure 4.** *Line plot (WPB% bands), patient 18 (LHS, good) and 28 (RHS, poor tracker).*
