A novel cardiovascular risk stratification model containing ECG and heart rate variability parameters for patients presenting to the emergency department with chest pain.

Heldeweg, M.L.A (Micah) (2015) A novel cardiovascular risk stratification model containing ECG and heart rate variability parameters for patients presenting to the emergency department with chest pain. thesis, Medicine.

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Abstract

Introduction Risk stratification models can be employed on the emergency department (ED) to evaluate patient prognosis and to guide choice of treatment. We derive and validate a new risk stratification model (SEDRSM) consisting of vital signs, heart rate variability (HRV) parameters, demographics, and ECG variables. Methods We conducted a single cohort, single center, observational study of patients presenting to the ED with chest pain. All patients above 21 years of age in sinus rhythm were eligible. ECGs were collected and evaluated for 12-lead ECG abnormalities. Routine monitoring ECG data was processed to obtain HRV parameters. Vital signs and demographics were obtained from electronic medical records. Thirty-day MACE (death, acute myocardial infarction, and revascularization) was chosen as the primary endpoint. A univariate analysis was used to identify candidate variables, and a multivariate logistic regression was used to derive the model for the final risk score. We compared the performance of SEDRSM with that of the TIMI score using AUROC. Results A total of 763 patients was included in this study, of which 254 (33%) met the primary endpoint. A total of 19 candidate predictors were entered into the multivariate model for backward variable elimination. The final model contained 10 clinical variables. SEDRSM outperformed the TIMI score for the prediction of MACE (AUROC of 0.783 versus 0.653) Discussion In this study we present a non-invasive and objective ECG-based risk stratification tool, applicable to patients presenting to the ED with chest pain. SEDRSM performed well versus the TIMI score, but future research warrants the use of an external validation cohort.

Item Type:	Thesis (Thesis)
Supervisor name:	Harms, Dr. Mark MD and Department of Internal Medicine and University Medical Centre Groningen
Supervisor name:	Ong Eng Hock, Prof. Marcus MD and Nan, Dr. Liu PhD (local/secondary supervisor) and Department of Emergency Medicine and Singapore General Hospital
Faculty:	Medical Sciences
Date Deposited:	25 Jun 2020 10:44
Last Modified:	25 Jun 2020 10:44
URI:	https://umcg.studenttheses.ub.rug.nl/id/eprint/535

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