Should lethal arrhythmias in hypertrophic cardiomyopathy be predicted using non-electrophysiological methods?

Accurate diagnosis of apical hypertrophic cardiomyopathy using explainable advanced electrocardiogram analysis

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.

Validation of the HCM Risk-SCD model in patients with hypertrophic cardiomyopathy and future perspectives

BACKGROUND

The hypertrophic cardiomyopathy (HCM) risk- sudden cardiac death (SCD) model provides a convenient tool for determining the risk of SCD in patients with HCM even though some patients with low-risk scores still remain at risk of SCD. Hence, the aim of our study was to assess the performance of HCM Risk-SCD in a large series of consecutive patients with HCM who had been followed up in a tertiary center.

METHODS

The study population consisted of 389 consecutive HCM patients who had been followed up between 2004 and 2021. Demographic and clinical characteristics, estimated 5-year risk using the HCM Risk-SCD model, were compiled, and survival data were collected during follow-up. Patients were divided into 2 groups according to their long-term survival, and HCM risk-SCD scores of these two groups were compared.

RESULTS

The long-term mortality was observed in 47 patients out of 389 patients in the during a mean follow-up of 55.5 ± 12.7 months. The mean HCM Risk-SCD score of surviving patients was significantly lower than that of non-survivors (1.8% vs. 3.0%, p < .001). The HCM Risk-SCD score was above 6% in nine (2.6%) survivors and nine (19.1%) non-survivors (p < .001). The ROC curve based on the HCM Risk-SCD score had 61% sensitivity and 61% specificity for risk threshold of for 2.0%, 38% sensitivity and 99% specificity a threshold of ≥4%, 17% sensitivity, and 99% specificity for a threshold of ≥6%.

CONCLUSION

A new risk algorithm with higher sensitivity is needed, although the HCM risk-SCD model is still quite useful in identifying patients at a high risk for SCD.

Risk stratification of sudden cardiac death: a review

Sudden cardiac death (SCD) is responsible for several millions of deaths every year and remains a major health problem. To reduce this burden, diagnosing and identification of high-risk individuals and disease-specific risk stratification are essential. Treatment strategies include treatment of the underlying disease with lifestyle advice and drugs and decisions to implant a primary prevention implantable cardioverter-defibrillator (ICD) and perform ablation of the ventricles and novel treatment modalities such as left cardiac sympathetic denervation in rare specific primary electric diseases such as long QT syndrome and catecholaminergic polymorphic ventricular tachycardia. This review summarizes the current knowledge on SCD risk according to underlying heart disease and discusses the future of SCD prevention.