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Background Data on the use of the wearable cardioverter‐defibrillator (WCD) among patients with myocarditis remain sparse. Consequently, evidence for guideline recommendations in this patient population is lacking. Methods and Results In total, 1596 consecutive patients were included in a multicenter registry from 8 European centers, with 124 patients (8%) having received the WCD due to myocarditis and reduced left ventricular ejection fraction or prior ventricular tachyarrhythmia. The mean age was 51.6±16.3 years, with 74% being male. Patients were discharged after index hospitalization on heart failure medication: Angiotensin‐converting enzyme inhibitors (62.5%), angiotensin‐receptor‐neprilysin inhibitor (22.9%), aldosterone‐antagonists (51%), or beta blockers (91.4%). The initial median left ventricular ejection fraction was 30% (22%–45%) and increased to 48% (39%–55%) over long‐term follow‐up (P

Abstract Aims Preventing hospitalization by detecting early evidence of heart failure (HF) decompensation in an outpatient setting can improve patient's quality of life and reduce costs of care. The purpose of this study was to assess the value of cardiac acoustic biomarkers (CABs), a combination of cardiohaemic vibrations synchronized with ECG signals, and heart rate (HR) for detecting HF decompensation during first 3 months after hospital discharge for HF. Methods and results Patients with an ejection fraction ≤35% (HFrEF) and hospitalized for decompensated HF were enrolled in a prospective observational study. All subjects wore a wearable cardioverter‐defibrillator (ZOLL LifeVest®, Pittsburgh, PA, USA) that is capable of recording CABs and HR. The primary endpoint of the study was the first HF event, defined as HF readmission or HF emergency room visit. From June 2017 through August 2019, 671 patients with HFrEF were enrolled. Eighty‐one patients (12.1%) had a total of 112 HF events. The algorithm detected HF events with a median of 32 days (interquartile range = 11‐45) in advance of the first HF event. The algorithm had a sensitivity of 69%, specificity of 60%, positive predictive value of 19%, and a negative predictive value of 94%. Of note, the baseline (first 7 days post‐enrolment) algorithm using CABs and HR was superior to New York Heart Association classification in detecting patients more likely to have HF decompensation (sensitivity and specificity of 61% and 68% vs. 46% and 55%, respectively). Conclusions This prospective international registry showed that an algorithm incorporating CABs and HR data detected HF events 30 days in advance of the event in patients with HFrEF during first 3 months after hospital discharge. Therefore, integrating CAB technology into clinical practice may prevent HF rehospitalizations.