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Are Anesthesiology Providers Good Guessers? Heart Rate and Oxygen Saturation Estimation in a Simulation Setting.

ABSTRACT: Background:Anesthesia providers may need to interpret the output of vital sign monitors based on auditory cues, in the context of multitasking in the operating room. This study aims to evaluate the ability of different anesthesia providers to estimate heart rate and oxygen saturation in a simulation setting. Methods:Sixty anesthesia providers (residents, nurse anesthetics, and anesthesiologists) were studied. Four scenarios were arranged in a simulation context. Two baseline scenarios with and without waveform visual aid, and two scenarios with variation of heart rate and/or oxygen saturation were used to assess the accuracy of the estimation made by the participants. Results:When the accurate threshold for the heart rate was set at less than 5 beats per minute, the providers only had a correct estimation at two baseline settings with visual aids (p=0.22 and 0.2237). Anesthesia providers tend to underestimate the heart rate when it increases. Providers failed to accurately estimate oxygen saturation with or without visual aid (p=0.0276 and 0.0105, respectively). Change in recording settings significantly affected the accuracy of heart rate estimation (p < 0.0001), and different experience levels affected the estimation accuracy (p=0.041). Conclusion:The ability of anesthesia providers with different levels of experience to assess baseline and variations of heart rate and oxygen saturation is unsatisfactory, especially when oxygen desaturation and bradycardia coexist, and when the subject has less years of experience.

SUBMITTER: Riveros Perez E

PROVIDER: S-EPMC6679872 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Are Anesthesiology Providers Good Guessers? Heart Rate and Oxygen Saturation Estimation in a Simulation Setting.

Riveros Perez Efrain E Jimenez Enoe E Albo Camila C Sanghvi Yashi Y Yang Nianlan N Rocuts Alexander A

Anesthesiology research and practice 20190721

<h4>Background</h4>Anesthesia providers may need to interpret the output of vital sign monitors based on auditory cues, in the context of multitasking in the operating room. This study aims to evaluate the ability of different anesthesia providers to estimate heart rate and oxygen saturation in a simulation setting.<h4>Methods</h4>Sixty anesthesia providers (residents, nurse anesthetics, and anesthesiologists) were studied. Four scenarios were arranged in a simulation context. Two baseline scena ...[more]

PMID: 31428146

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Project description:ObjectiveHighly comparative time series analysis (HCTSA) is a novel approach involving massive feature extraction using publicly available code from many disciplines. The Prematurity-Related Ventilatory Control (Pre-Vent) observational multicenter prospective study collected bedside monitor data from > 700 extremely preterm infants to identify physiologic features that predict respiratory outcomes. We calculated a subset of 33 HCTSA features on > 7M 10-minute windows of oxygen saturation (SPO2) and heart rate (HR) from the Pre-Vent cohort to quantify predictive performance. This subset included representatives previously identified using unsupervised clustering on > 3500 HCTSA algorithms. Performance of each feature was measured by individual area under the receiver operating curve (AUC) at various days of life and binary respiratory outcomes. These were compared to optimal PreVent physiologic predictor IH90 DPE, the duration per event of intermittent hypoxemia events with threshold of 90%.Main resultsThe top HCTSA features were from a cluster of algorithms associated with the autocorrelation of SPO2 time series and identified low frequency patterns of desaturation as high risk. These features had comparable performance to and were highly correlated with IH90_DPE but perhaps measure the physiologic status of an infant in a more robust way that warrants further investigation. The top HR HCTSA features were symbolic transformation measures that had previously been identified as strong predictors of neonatal mortality. HR metrics were only important predictors at early days of life which was likely due to the larger proportion of infants whose outcome was death by any cause. A simple HCTSA model using 3 top features outperformed IH90_DPE at day of life 7 (.778 versus .729) but was essentially equivalent at day of life 28 (.849 versus .850). These results validated the utility of a representative HCTSA approach but also provides additional evidence supporting IH90_DPE as an optimal predictor of respiratory outcomes.

Dataset Information

Are Anesthesiology Providers Good Guessers? Heart Rate and Oxygen Saturation Estimation in a Simulation Setting.

Publications

Are Anesthesiology Providers Good Guessers? Heart Rate and Oxygen Saturation Estimation in a Simulation Setting.

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