Baseline and Dynamic Risk Predictors of Appropriate Implantable Cardioverter Defibrillator Therapy.

ABSTRACT: Background Current approaches fail to separate patients at high versus low risk for ventricular arrhythmias owing to overreliance on a snapshot left ventricular ejection fraction measure. We used statistical machine learning to identify important cardiac imaging and time-varying risk predictors. Methods and Results Three hundred eighty-two cardiomyopathy patients (left ventricular ejection fraction ≤35%) underwent cardiac magnetic resonance before primary prevention implantable cardioverter defibrillator insertion. The primary end point was appropriate implantable cardioverter defibrillator discharge or sudden death. Patient characteristics; serum biomarkers of inflammation, neurohormonal status, and injury; and cardiac magnetic resonance-measured left ventricle and left atrial indices and

SUBMITTER: Wu KC 

PROVIDER: S-EPMC7763383 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature