Hughes, RK;
Thornton, GD;
Malcolmson, JW;
Pierce, I;
Khoury, S;
Hornell, A;
Knott, K;
Captur, G;
Moon, JC;
Schlegel, TT;
et al.
Hughes, RK; Thornton, GD; Malcolmson, JW; Pierce, I; Khoury, S; Hornell, A; Knott, K; Captur, G; Moon, JC; Schlegel, TT; Ugander, M
(2024)
Accurate diagnosis of apical hypertrophic cardiomyopathy using explainable advanced electrocardiogram analysis.
Europace, 26 (4).
euae093.
ISSN 1532-2092
https://doi.org/10.1093/europace/euae093
SGUL Authors: Khoury, Shafik
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Abstract
AIMS: Typical electrocardiogram (ECG) features of apical hypertrophic cardiomyopathy (ApHCM) include tall R waves and deep or giant T-wave inversion in the precordial leads, but these features are not always present. The ECG is used as the gatekeeper to cardiac imaging for diagnosis. We tested whether explainable advanced ECG (A-ECG) could accurately diagnose ApHCM. METHODS AND RESULTS: Advanced ECG analysis was performed on standard resting 12-lead ECGs in patients with ApHCM [n = 75 overt, n = 32 relative (<15 mm hypertrophy); a subgroup of which underwent cardiovascular magnetic resonance (n = 92)], and comparator subjects (n = 2449), including healthy volunteers (n = 1672), patients with coronary artery disease (n = 372), left ventricular electrical remodelling (n = 108), ischaemic (n = 114) or non-ischaemic cardiomyopathy (n = 57), and asymmetrical septal hypertrophy HCM (n = 126). Multivariable logistic regression identified four A-ECG measures that together discriminated ApHCM from other diseases with high accuracy [area under the receiver operating characteristic (AUC) curve (bootstrapped 95% confidence interval) 0.982 (0.965-0.993)]. Linear discriminant analysis also diagnosed ApHCM with high accuracy [AUC 0.989 (0.986-0.991)]. CONCLUSION: Explainable A-ECG has excellent diagnostic accuracy for ApHCM, even when the hypertrophy is relative, with A-ECG analysis providing incremental diagnostic value over imaging alone. The electrical (ECG) and anatomical (wall thickness) disease features do not completely align, suggesting that future diagnostic and management strategies may incorporate both features.
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