Electrocardiographic parameter profiles for differentiating hypertrophic cardiomyopathy stages.

ABSTRACT:

Background

The efficacy of artificial intelligence (AI)-enhanced electrocardiography (ECG) for detecting hypertrophic cardiomyopathy (HCM) and its dilated phase (dHCM) has been developed, though specific ECG characteristics associated with these conditions remain insufficiently characterized.

Methods

This retrospective study included 19,170 patients, with 140 HCM or dHCM cases, from the Shinken Database (2010-2017). The 140 cases (HCM-total) were categorized into basal-only HCM (HCM-basal, n = 75), apical involvement (HCM-apical, n = 46), and dHCM (n = 19). We analyzed 438 ECG parameters across the P-wave (110), QRS complex (194), and ST-T segment (134). High parameter importance (HPI) was defined as 1/p > 10⁴ in univariate logistic reg

SUBMITTER: Hirota N 

PROVIDER: S-EPMC11876995 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature