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

Sumeet S. Chugh, Kyndaron Reinier, Audrey Uy-Evanado, Harpriya S. Chugh, David Elashoff, Christopher Young, Angelo Salvucci, Jonathan Jui

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)411-423
Number of pages13
JournalJACC: Clinical Electrophysiology
Volume8
Issue number4
DOIs
StatePublished - Apr 2022
Externally publishedYes

Keywords

  • cardiac arrest
  • prevention
  • risk stratification
  • sudden cardiac death
  • ventricular fibrillation

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Physiology (medical)

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