Dataset Information

Heart Rate Variability and Acute Stress Among Novice Airway Managers.

ABSTRACT: Background:The nature of medical emergencies places emergency physicians at risk for high levels of acute psychological stress (APS). Stress-modifying techniques like visualization, breath control, and mental practice may help mitigate APS, but objective markers of stress are difficult to measure in the clinical setting. We explored the relationship between heart rate variability (HRV), a real-time measure of autonomic arousal, and self-reported APS among emergency medicine (EM) residents learning to intubate on actual patients. Methods:This was a prospective study of postgraduate year 1 (PGY-1) EM residents at a single academic medical center during their 1-month anesthesia rotation. We obtained repeated measures of HRV immediately before and during the first intubation attempt each day. Participants completed the modified Spielberger State-Trait Anxiety Inventory (STAI-6) before intubation attempts and scored intubation difficulty using the Intubation Difficulty Scale. We analyzed HRV using root mean square of successive differences and analyzed data using clustered data methods and Pearson correlation coefficients. Results:We enrolled eight PGY-1 residents and recorded 64 intubations. Mean HRV in the 2 minutes before intubation (17.88 ± 9.22) and during intubation (21.17 ± 13.46) was significantly lower than resting baseline (32.09 ± 15.23; adjusted mean difference [95% CI] = -13.90 [-20.35 to -7.45], p < 0.001; and -10.77 [-17.65 to -3.88], p = 0.02). Preintubation anxiety was negatively correlated with HRV (r = -0.39 [-0.58 to -0.16], p = 0.001). Intubation difficulty was not significantly correlated with HRV (r = -0.12 [-0.36 to 0.13], p = 0.35). Conclusions:HRV shows promise as a real-time index of autonomic arousal and may serve as an outcome measure in the evaluation of stress-modifying interventions.

SUBMITTER: Mefford JM

PROVIDER: S-EPMC6637011 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Heart Rate Variability and Acute Stress Among Novice Airway Managers.

Mefford Jason M JM Kahle Sarah S Gupta Shikha S Tancredi Daniel D Danielson Aaron R AR Clarke Samuel O SO

AEM education and training 20190328 3

<h4>Background</h4>The nature of medical emergencies places emergency physicians at risk for high levels of acute psychological stress (APS). Stress-modifying techniques like visualization, breath control, and mental practice may help mitigate APS, but objective markers of stress are difficult to measure in the clinical setting. We explored the relationship between heart rate variability (HRV), a real-time measure of autonomic arousal, and self-reported APS among emergency medicine (EM) resident ...[more]

PMID: 31360823

Similar Datasets

Project description:BackgroundUsing Ambient Assisted Living sensors to detect acute stress could help people mitigate the harmful effects of everyday stressful situations. This would help both the healthy and those affected more by sudden stressors, e.g., people with diabetes or heart conditions. The study aimed to develop a method for providing reliable stress detection based on heart rate variability features extracted from portable devices.MethodsFeatures extracted from portable electrocardiogram sensor recordings were used for training various classification algorithms for stress detection purposes. Data were recorded in a clinical trial with 7 participants and two stressors, the Trier Social Stress Test and the Stroop colour word test, both validated by standardised questionnaires. Different heart rate variability feature sets (all, time-domain and non-linear only, frequency-domain only) were tested to investigate how classification performance is affected, in addition to various time window length setups and participant-wise training sessions. The accuracy and F1 score of the trained models were compared and analysed.ResultsThe best results were achieved with models using time-domain and non-linear heart rate variability features with 5-min-long overlapping time windows, yielding 96.31% accuracy and 96.26% F1 score. Shorter overlapping windows had slightly lower performance, with 91.62-94.55% accuracy and 91.77-94.55% F1 score ranges. Non-overlapping window configurations were less effective, with both accuracy and F1 score below 88%. For participant-wise learning, average F1 scores of 99.47%, 98.93% and 96.1% were achieved for feature sets using all, time-domain and non-linear, and frequency-domain features, respectively.ConclusionThe tested stress detector models based on heart rate variability data recorded by a single electrocardiogram sensor performed just as well as those published in the literature working with multiple sensors, or even better. This suggests that once portable devices such as smartwatches provide reliable hear rate variability recordings, efficient stress detection can be achieved without the need for additional physiological measurements.

Project description:The brain continuously receives input from the internal and external environment. Using this information, the brain exerts its influence on both itself and the body to facilitate an appropriate response. The dynamic interplay between the brain and the heart and how external conditions modulate this relationship deserves attention. In high-stress situations, synchrony between various brain regions such as the prefrontal cortex and the heart may alter. This flexibility is believed to facilitate transitions between functional states related to cognitive, emotional, and especially autonomic activity. This study examined the dynamic temporal functional association of heart rate variability (HRV) with the interaction between three main canonical brain networks in 38 healthy male subjects at rest and directly after a psychosocial stress task. A sliding window approach was used to estimate the functional connectivity (FC) among the salience network (SN), central executive network (CEN), and default mode network (DMN) in 60-s windows on time series of blood-oxygen-level dependent (BOLD) signal. FC between brain networks was calculated by Pearson correlation. A multilevel linear mixed model was conducted to examine the window-by-window association between the root mean square of successive differences between normal heartbeats (RMSSD) and FC of network-pairs across sessions. Our findings showed that the minute-by-minute correlation between the FC and RMSSD was significantly stronger between DMN and CEN than for SN and CEN in the baseline session [b = 4.36, t(5025) = 3.20, p = 0.006]. Additionally, this differential relationship between network pairs and RMSSD disappeared after the stress task; FC between DMN and CEN showed a weaker correlation with RMSSD in comparison to baseline [b = -3.35, t(5025) = -3.47, p = 0.006]. These results suggest a dynamic functional interplay between HRV and the functional association between brain networks that varies depending on the needs created by changing conditions.

Project description:Simulation is regarded as an effective educational method for the delivery of clinical scenarios. However, exposure to unfamiliar environments during simulation can cause excessive stress among students, possibly leading to unnatural speech/behavior and poor skill learning (Yerkes-Dodson's law). Thus, assessing students' stress in a simulation can provide educators with a better understanding of their mental state. This study sought to clarify stress changes throughout the progression of the simulation by measuring heart rate variability and students' subjective reactions in 74 nursing students. Heart rate variability was calculated in terms of its high-frequency (HF) and low-frequency/high-frequency (LF/HF) components during 4 phases-the break, patient care, reporting, and debriefing. Students were interviewed about stress experienced during the simulation. The results showed that HF decreased significantly from the break to the patient care and reporting phases. Furthermore, LF/HF increased significantly from the break to the reporting phases. Approximately 55 students felt stressed during the simulation, 24 of whom felt most stressed during the reporting phase. Therefore, the reporting phase involved high objective and subjective stress. It may be possible that the educator's evaluative attitude increased students' stress. Therefore, a stress intervention during the reporting phase might further improve students' performance during that phase. The debriefing phase did not significantly differ from the break phase for objective stress, and students did not report feeling stressed. Thus, in this phase, they were released from the stress of the reporting phase and the unfamiliar environment. During this phase, they might be able to learn what they could not understand owing to high stress in the patient care and reporting phases. This study provides objective and subjective evidence of students' stress during simulation, and indicates the necessity of providing support during the reporting phase and the importance of debriefing when using clinical scenarios for teaching clinical skills.

Dataset Information

Heart Rate Variability and Acute Stress Among Novice Airway Managers.

Publications

Heart Rate Variability and Acute Stress Among Novice Airway Managers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets