Improved prediction of sudden cardiac death in patients with heart failure through digital processing of electrocardiography.

ABSTRACT:

Aims

Available predictive models for sudden cardiac death (SCD) in heart failure (HF) patients remain suboptimal. We assessed whether the electrocardiography (ECG)-based artificial intelligence (AI) could better predict SCD, and also whether the combination of the ECG-AI index and conventional predictors of SCD would improve the SCD stratification among HF patients.

Methods and results

In a prospective observational study, 4 tertiary care hospitals in Tokyo enrolled 2559 patients hospitalized for HF who were successfully discharged after acute decompensation. The ECG data during the index hospitalization were extracted from the hospitals' electronic medical record systems. The association of the ECG-AI index and SCD was evaluated with adjustment for left ventricular ejection

SUBMITTER: Shiraishi Y 

PROVIDER: S-EPMC10062335 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature