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. 2025 Mar 4;41(2):e70031.
doi: 10.1002/joa3.70031. eCollection 2025 Apr.

Electrocardiographic parameter profiles for differentiating hypertrophic cardiomyopathy stages

Affiliations

Electrocardiographic parameter profiles for differentiating hypertrophic cardiomyopathy stages

Naomi Hirota et al. J Arrhythm. .

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 regression, while multivariate logistic regression was used to determine the area under the receiver operating characteristic curves (AUROC).

Results: In HCM-basal and HCM-apical, HPI was predominantly observed in the ST-T segment (49% and 51%, respectively), followed by the QRS complex (29% and 27%). For dHCM, HPI was lower in the ST-T segment (16%) and QRS complex (22%). The P-wave had low HPI across all subtypes. AUROCs for models with total ECG parameters were 0.925 for HCM-basal, 0.981 for HCM-apical, and 0.969 for dHCM. While AUROCs for the top 10 HPI models were lower than the total ECG parameter model for HCM total, they were comparable across HCM subtypes.

Conclusions: As HCM progresses to dHCM, a shift in HPI from the ST-T segment to the QRS complex provides clinically relevant insights. For HCM subtypes, the top 10 ECG parameters yield predictive performance similar to the full parameter set, supporting efficient approaches for AI-based diagnostic models.

Keywords: diagnostic modeling; dilated phase hypertrophic cardiomyopathy; disease progression; electrocardiogram parameters; hypertrophic cardiomyopathy.

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Conflict of interest statement

Dr. Suzuki received lecture fees from Daiichi Sankyo and Bristol‐Myers Squibb. Dr. Yamashita received research funds and/or lecture fees from Daiichi Sankyo, Bayer Yakuhin, Bristol‐Myers Squibb, Pfizer, Nippon Boehringer Ingelheim, Eisai, Mitsubishi Tanabe Pharm, Ono Pharmaceutical, and Toa Eiyo.

Figures

FIGURE 1
FIGURE 1
Distribution of ECG parameter importance. (A) HCM total, (B) HCM‐basal, (C) HCM‐apex, and (D) dHCM. Parameter importance is represented as the reciprocal of the p‐value (1/p) derived from univariate models using each ECG parameter. 1/p, reciprocal p‐value; dHCM, dilated phase hypertrophic cardiomyopathy; HCM, hypertrophic cardiomyopathy; HCM‐apical, HCM with hypertrophy involving the apex; HCM‐basal, HCM with basal hypertrophy only; P, P‐wave; QRS, QRS complex; ST‐T, ST‐T segment.
FIGURE 2
FIGURE 2
ROC curves of prediction models for each distinct disease label (A: HCM total, B: HCM‐basal, C: HCM‐apex, and D: dHCM) and AUCs for each model (E), using total parameters as well as parameters specific to the P‐wave, QRS complex, and ST‐T segment. 1/p, reciprocal p‐value; AUC, area under the curve; dHCM, dilated phase hypertrophic cardiomyopathy; HCM, hypertrophic cardiomyopathy; HCM‐apical, HCM with hypertrophy involving the apex; HCM‐basal, HCM with basal hypertrophy only; P, P‐wave; QRS, QRS complex; ROC, receiver operating characteristic; ST‐T, ST‐T segment.
FIGURE 3
FIGURE 3
Incremental changes in AUCs of prediction models from the top 5 parameters to the top 10 parameters and total parameters for each distinct disease label (blue line: HCM total, orange line: HCM‐basal, gray line: HCM‐apex, and yellow line: dHCM). 1/p, reciprocal p‐value; AUC, area under the curve; dHCM, dilated phase hypertrophic cardiomyopathy; HCM, hypertrophic cardiomyopathy; HCM‐apical, HCM with hypertrophy involving the apex; HCM‐basal, HCM with basal hypertrophy only; P, P‐wave; QRS, QRS complex; ROC, receiver operating characteristic; ST‐T, ST‐T segment.

References

    1. Maron BJ, Haas TS, Murphy CJ, Ahluwalia A, Rutten‐Ramos S. Incidence and causes of sudden death in U.S. college athletes. J Am Coll Cardiol. 2014;63(16):1636–1643. - PubMed
    1. Maron BJ. Risk stratification and role of implantable defibrillators for prevention of sudden death in patients with hypertrophic cardiomyopathy. Circ J. 2010;74(11):2271–2282. - PubMed
    1. Maron BJ. Clinical course and Management of Hypertrophic Cardiomyopathy. N Engl J Med. 2018;379(7):655–668. - PubMed
    1. Maron BJ. Hypertrophic cardiomyopathy: a systematic review. JAMA. 2002;287(10):1308–1320. - PubMed
    1. Maron BJ, Rowin EJ, Casey SA, Maron MS. How hypertrophic cardiomyopathy became a contemporary treatable genetic disease with low mortality: shaped by 50 years of clinical research and practice. JAMA Cardiol. 2016;1(1):98–105. - PubMed