Integrating heart rate variability, vital signs, electrocardiogram, and troponin to triage chest pain patients in the ED.

BACKGROUND: Current triage methods for chest pain patients typically utilize symptoms, electrocardiogram (ECG), and vital sign data, requiring interpretation by dedicated triage clinicians. In contrast, we aimed to create a quickly obtainable model integrating the objective parameters of heart rate variability (HRV), troponin, ECG, and vital signs to improve accuracy and efficiency of triage for chest pain patients in the emergency department (ED).

METHODS: Adult patients presenting to the ED with chest pain from September 2010 to July 2015 were conveniently recruited. The primary outcome was a composite of revascularization, death, cardiac arrest, cardiogenic shock, or lethal arrhythmia within 72-h of presentation to the ED. To create the chest pain triage (CPT) model, logistic regression was done where potential covariates comprised of vital signs, ECG parameters, troponin, and HRV measures. Current triage methods at our institution and modified early warning score (MEWS) were used as comparators.

RESULTS: A total of 797 patients were included for final analysis of which 146 patients (18.3%) met the primary outcome. Patients were an average age of 60years old, 68% male, and 56% triaged to the most acute category. The model consisted of five parameters: pain score, ST-elevation, ST-depression, detrended fluctuation analysis (DFA) α1, and troponin. CPT model>0.09, CPT model>0.15, current triage methods, and MEWS≥2 had sensitivities of 86%, 74%, 75%, and 23%, respectively, and specificities of 45%, 71%, 48%, and 78%, respectively.

CONCLUSION: The CPT model may improve current clinical triage protocols for chest pain patients in the ED.