Anesthetists’ Heart Rate Variability as an Indicator of Performance During Induction of General Anesthesia and Simulated Critical Incidents

Abstract

Abstract. In the environment of anesthesia, good performance describes the absence of threat for the patient as well as a quick reaction to challenging and possibly life-threatening circumstances. Elsewhere, performance and cognitive function have been linked to indicators of vagally-mediated heart rate variability (HRV). This exploratory study examines the correlation between anesthetists’ HRV and their performance during uneventful induction of general anesthesia and during a simulated critical incident. For this study electrocardiograms (ECG) were obtained from two different groups of anesthetists providing general anesthesia in uneventful real cases in the operation room (OR, n = 38) and during the management of a hypotension scenario in a high-fidelity human patient simulator environment (SIM, n = 23). Frequency, time domain, and nonlinear HRV metrics were calculated from 5-min ECG recordings. To separate high performing (HP) and low performing (LP) individuals, the time needed for induction (in the OR setting) and the length and depth of hypotension (in the SIM setting) were used as performance correlates. The Mann-Whitney- U-test was used to assess differences in HRV within the groups. In both settings (OR and SIM), linear and nonlinear HRV metrics did not differ significantly between the HP and LP group. Also, the anesthetists’ work experience and sex were not related to performance. While providing general anesthesia and during a simulated critical incident, high and low performing individuals do not differ with respect to HRV metrics, sex, and work experience. Further research including the HRV under resting conditions is necessary.

Differences in beginner and expert neurointerventionalists” heart rate variability during simulated neuroangiographies

“…However, our findings are supported by larger studies. 12,16 And we thus do not think that the sample size effected our results. Second, in line with previous work 12,16 and the neurovisceral integration model, 17 we did not account for age corrections.…”

“…12,16 And we thus do not think that the sample size effected our results. Second, in line with previous work 12,16 and the neurovisceral integration model, 17 we did not account for age corrections. However, the multivariate regression model showed that the differences we observed were significantly associated with experience and not age.…”

“…Nonetheless, high shares of HF components have been found in inferior groups, before. 16 Elliot and Colleagues linked decreased HF activity to worse IQ performance. 27 For our sample, however, decreased HF components (and thus, according to Elliot and colleagues diminished IQ performance) might simply equal a more automated course of action within the more experienced participants.…”

“…To date, HRV metrics have been extensively studied insimulator environments from combat flight and aviation 28 – 30 to medical simulation. 16 Yet, differences between experts and beginners have only seldom been investigated. Conversely, these differences are majorly important for a potential use of HRV metrics to prevent harmful events: When there is need to detect the risk of work overload, it is meaningful to define a threshold between experts and beginners.…”

“…8,[10][11][12][13] According to the situational awareness framework, an explanation for the impact of work experience on performance is that more experienced subjects develop sophisticated mental models and automatisms for information-procession, and therefore have additional cognitive spare capacity for the challenges of an unknown situation. [14][15][16] According to the neurovisceral integration model proposed by Thayer and colleagues, these mental models and spare capacities might be represented by vagally-mediated HRV metrics since they are correlates of cognitive performance, and especially index prefrontal neuronal activity. 17 Such vagally-mediated HRV metrics are predominately found among the frequency-domain HRV metrics; i.e., these measures of HRV that are calculated based on the power spectral density of the signal.…”