ABSTRACT
Objective@#Suicide is the 2nd leading cause of death in adolescence, and acute pediatric mental health emergency department (ED) visits have doubled in the past decade. The objective of this study was to evaluate physiologic parameters relationship to suicide severity. @*Methods@#This was a prospective, observational study from April 2018 thru November 2019 in a tertiary care pediatric emergency department (ED) and inpatient pediatric psychiatric unit enrolling acutely suicidal adolescent patients. Patients wore a wrist device that used photoplethysmography for 7 days during their acute hospitalization to measure heart rate variability (HRV). During that time, Columbia Suicide Severity Scores (CSSRS) were assessed at 3 time points. @*Results@#There was complete device data and follow-up for 51 patients. There was an increase in the high frequency (HF) component of HRV in patients that had a 25% or greater decrease in their CSSRS (mean difference 11.89 ms/ Hz ; p-value 0.005). Patients with a CSSRS≥15 on day of enrollment had a lower, although not statistically significant, HF component (mean difference -8.34 ms/ Hz; p-value 0.071). @*Conclusion@#We found an inverse correlation between parasympathetic activity measured through the HF component and suicidality in an acutely suicidal population of adolescents. Wearable technology may have the ability to improve outpatient monitoring for earlier detection and intervention.
ABSTRACT
Objective@#Heart rate variability (HRV) evaluates small beat-to-beat time interval (BBI) differences produced by the heart and suggested as a marker of the autonomic nervous system. Artifact produced by movement with wrist worn devices can significantly impact the validity of HRV analysis. The objective of this study was to determine the impact of small errors in BBI selection on HRV analysis and produce a foundation for future research in mental health wearable technology. @*Methods@#This was a sub-analysis from a prospective observational clinical trial registered with clinicaltrials.gov (NCT03030924). A cohort of 10 subject’s HRV tracings from a wearable wrist monitor without any artifact were manipulated by the study team to represent the most common forms of artifact encountered. @*Results@#Root mean square of successive differences stayed below a clinically significant change when up to 5 beats were selected at the wrong time interval and up to 36% of BBIs was removed. Standard deviation of next normal intervals stayed below a clinically significant change when up to 3 beats were selected at the wrong time interval and up to 36% of BBIs were removed. High frequency HRV shows significant changes when more than 2 beats were selected at the wrong time interval and any BBIs were removed. @*Conclusion@#Time domain HRV metrics appear to be more robust to artifact compared to frequency domains. Investigators examining wearable technology for mental health should be aware of these values for future analysis of HRV studies to improve data quality.