Prediction of Sudden Cardiac Death Manifesting With Documented Ventricular Fibrillation or Pulseless Ventricular Tachycardia.

OBJECTIVES

This study aimed to develop a novel clinical prediction algorithm for avertable sudden cardiac death.

BACKGROUND

Sudden cardiac death manifests as ventricular fibrillation (VF)/ ventricular tachycardia (VT) potentially treatable with defibrillation, or nonshockable rhythms (pulseless electrical activity/asystole) with low likelihood of survival. There are no available clinical risk scores for targeted prediction of VF/VT.

METHODS

Subjects with out-of-hospital sudden cardiac arrest presenting with documented VF or pulseless VT (33% of total cases) were ascertained prospectively from the Portland, Oregon, metro area with population ≈1 million residents (n = 1,374, 2002-2019). Comparisons of lifetime clinical records were conducted with a control group (n = 1,600) with ≈70% coronary disease prevalence. Prediction models were constructed from a training dataset using backwards stepwise logistic regression and applied to an internal validation dataset. Receiver operating characteristic curves (C statistic) were used to evaluate model discrimination. External validation was performed in a separate, geographically distinct population (Ventura County, California, population ≈850,000, 2015-2020).

RESULTS

A clinical algorithm (VFRisk) constructed with 13 clinical, electrocardiogram, and echocardiographic variables had very good discrimination in the training dataset (C statistic = 0.808; [95% CI: 0.774-0.842]) and was successfully validated in internal (C statistic = 0.776 [95% CI: 0.725-0.827]) and external (C statistic = 0.782 [95% CI: 0.718-0.846]) datasets. The algorithm substantially outperformed the left ventricular ejection fraction (LVEF) ≤35% (C statistic = 0.638) and performed well across the LVEF spectrum.

CONCLUSIONS

An algorithm for prediction of sudden cardiac arrest manifesting with VF/VT was successfully constructed using widely available clinical and noninvasive markers. These findings have potential to enhance primary prevention, especially in patients with mid-range or preserved LVEF.

Informations de copyright

Copyright © 2022 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Funding Support and Author Disclosures Dr Chugh has received funding from National Institutes of Health, National Heart, Lung, and Blood Institute Grants R01HL126938 and R01HL145675 for this work; and holds the Pauline and Harold Price Chair in Cardiac Electrophysiology at Cedars-Sinai, Los Angeles. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.