An observational, prospective study exploring the use of heart rate variability as a predictor of clinical outcomes in pre-hospital ambulance patients.
OBJECTIVE
To explore the use of pre-hospital heart rate variability (HRV) as a predictor of clinical outcomes such as hospital admission, intensive care unit (ICU) admission and mortality. We also implemented an automated pre-analysis signal processing algorithm and multiple principal component analysis (PCA) for outcomes.


METHODS
We conducted a prospective observational clinical study at an emergency medical services (EMS) system in a medium sized urban setting in the United States. Electrocardiogram (ECG) data was obtained from a sample of 45 ambulance patients conveyed to a tertiary hospital, monitored with a LIFEPAK12 defibrillator/monitor. After extracting the data, filtering for noise reduction and isolating non-sinus beats, various HRV parameters were computed. These included time domain, frequency domain and geometric parameters. PCA was performed on the hospital outcomes for these patients.


RESULTS
We used a combination of HRV parameters, age and vital signs such as respiratory rate, SpO2 and Glasgow coma score (GCS) in a PCA analysis. For predicting admission to ICU, sensitivity was 100%, specificity was 48.6%, and negative predictive value (NPV) was 100%; for predicting admission to hospital, sensitivity was 78.9%, specificity was 85.7%, and NPV was 75.0%; for predicting death, sensitivity was 50.0%, specificity was 100%, and NPV was 97.4%. There was also a significant correlation of several HRV parameters with length of hospital stay.


CONCLUSIONS
With signal processing techniques, it is feasible to filter and analyze ambulance ECG data for HRV. We found a combination of HRV parameters and traditional 'vital signs' to have an association with clinical outcomes in pre-hospital patients. This may have potential as a triage tool for ambulance patients.
Department of Emergency Medicine, Singapore General Hospital, Singapore. marcus.ong.e.h@sgh.com.sg
Marcus Eng Hock
ME
Ong
Pavitra
P
Padmanabhan
Yiong Huak
YH
Chan
Zhiping
Z
Lin
Jerry
J
Overton
Kevin R
KR
Ward
Ding-Yu
DY
Fei
D000368:Aged; D000465:Algorithms; D000552:Ambulances; D003422:Critical Care; D004562:Electrocardiography; D005260:Female; D006339:Heart Rate / Q000502:physiology*; D006760:Hospitalization; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D025341:Principal Component Analysis; D011379:Prognosis; D011446:Prospective Studies; D012815:Signal Processing, Computer-Assisted