Abstract

BackgroundIt has been shown that linear and non-linear heart rate variability (HRV) metrics are suitable to assess workload of anesthetists administering anesthesia. In pre-hospital emergency care, these parameters have not yet been evaluated. We hypothesized that heart rate (HR) and HRV metrics discriminate between differing workload levels of an emergency physician.MethodsElectrocardiograms were obtained from 13 emergency physicians. Mean HR, ten linear and seven non-linear HRV metrics were analyzed. For each sortie, four different levels of workload were defined. Mixed-effects models and the area under the receiver operating characteristics curve (AUC) were used to test and quantify the HR and HRV metrics’ ability to discriminate between levels of workload. This was conducted for mean HR and each HRV metric as well as for groups of metrics (time domain vs. frequency domain vs. non-linear metrics).ResultsThe non-linear HRV metric Permutation entropy (PeEn) discriminated best between the time before the alarm and primary patient care (AUC = 0.998, 1st rank of 18 HRV metrics). In contrast, AUC of the mean HR was low (0.558, 17th rank). In the multivariable approach, the non-linear HRV metrics provided a higher AUC (0.998) compared to the frequency domain (0.677) and to the time domain metrics (0.680).ConclusionNon-linear heart rate metrics and, specifically, PeEn provided good validity for the assessment of different levels of a physician’s workload in the setting of pre-hospital emergency care. In contradiction to earlier findings, the physicians’ mean HR was not a valid marker of workload.

Highlights

  • Workload describes the balance between the challenges of a task and an individual’s response to them;[1] workload is known to increase with working memory load and during problem solving.[2]

  • The aforementioned study was limited to the highly-standardized work environment of the operation theatre with healthy patients presenting for minor limb surgery under general anesthesia

  • The non-linear heart rate variability (HRV) metrics, which are measurands of irregularities of the NN intervals,[33, 34] were superior to linear HRV metrics (i.e. HRV metrics of time and frequency domain; see Table 3). One of these non-linear HRV metrics, permutation entropy (PeEn), showed the highest AUC when comparing before the alarm to drive and primary care time, respectively (Table 2)

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Summary

Introduction

Workload describes the balance between the challenges of a task and an individual’s response to them;[1] workload is known to increase with working memory load and during problem solving.[2]. Anesthetists’ heart rate (HR) is a physiological correlate of workload and has been used in most studies that relied on an objective assessment method.[9,10,11] Recently, several linear and non-linear metrics of heart rate variability (HRV) have been identified to be promising tools to discriminate different levels of anesthetists’ workload in the operation theatre.[8] Among them, mean HR and permutation entropy (PeEn) performed best according to their area under the receiver operating characteristics curves (AUC). It has been shown that linear and non-linear heart rate variability (HRV) metrics are suitable to assess workload of anesthetists administering anesthesia. We hypothesized that heart rate (HR) and HRV metrics discriminate between differing workload levels of an emergency physician

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