The ESC Risk Score Is Less Reliable than ACC/AHA Risk Factors in Hypertrophic Cardiomyopathy: When Sensitivity Trumps Specificity

Validation of the new American College of Cardiology/American Heart Association Guidelines for the risk stratification of sudden cardiac death in a large Mediterranean cohort with Hypertrophic Cardiomyopathy

BACKGROUND

The aim of our study was to assess the performance of the new American College of Cardiology (ACC)/American Heart Association (AHA) Guidelines, with respect to sudden cardiac death (SCD) prevention, in comparison with the established risk score of the European Society of Cardiology (hypertrophic cardiomyopathy [HCM] Risk-SCD), in a large Mediterranean cohort of HCM patients.

METHODS

The clinical and imaging characteristics of 784 HCM patients (mean age at first evaluation 52 ± 16 years, 67.2% males) were analyzed retrospectively. The sensitivity, specificity, and negative predictive value for SCD events of the presence of ≥1 risk factor for SCD according to the ACC/AHA Guidelines 2020 and of the HCM Risk-SCD≥6% and HCM Risk-SCD≥4% were estimated during follow-up.

RESULTS

During follow-up, 47 (6%) patients suffered an SCD event. The presence of ≥1 major risk factor for SCD according to the new ACC/AHA Guidelines had 96% sensitivity (95% CI 85.5-99.5%) with modest specificity of 59% (95% CI 55-62.2%) and negative predictive value of 99.5% (95% CI 98.2-99.9%). On the contrary, HCM- Risk-SCD≥6% had a relatively low sensitivity (32%, 95% CI 19.1-47.1%) and high specificity of 95% (95% CI 93.1-96.4%), whereas, HCM-Risk-SCD≥4% had sensitivity of 60% (95% CI 44-74%) and specificity of 83.9% (95% CI 80-85.6%). Both the HCM Risk-SCD cut-off values demonstrated lower negative predictive value but higher accuracy than the ACC/AHA algorithm for SCD prediction.

CONCLUSION

The novel ACC/AHA proposed algorithm identifies most of the patients with an SCD event with the cost of numerous defibrillator implantations. HCM-Risk-SCD demonstrated higher specificity, whereas its sensitivity and negative predictive value are modest.

A Validated Model for Sudden Cardiac Death Risk Prediction in Pediatric Hypertrophic Cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy is the leading cause of sudden cardiac death (SCD) in children and young adults. Our objective was to develop and validate a SCD risk prediction model in pediatric hypertrophic cardiomyopathy to guide SCD prevention strategies.

METHODS

In an international multicenter observational cohort study, phenotype-positive patients with isolated hypertrophic cardiomyopathy <18 years of age at diagnosis were eligible. The primary outcome variable was the time from diagnosis to a composite of SCD events at 5-year follow-up: SCD, resuscitated sudden cardiac arrest, and aborted SCD, that is, appropriate shock following primary prevention implantable cardioverter defibrillators. Competing risk models with cause-specific hazard regression were used to identify and quantify clinical and genetic factors associated with SCD. The cause-specific regression model was implemented using boosting, and tuned with 10 repeated 4-fold cross-validations. The final model was fitted using all data with the tuned hyperparameter value that maximizes the c-statistic, and its performance was characterized by using the c-statistic for competing risk models. The final model was validated in an independent external cohort (SHaRe [Sarcomeric Human Cardiomyopathy Registry], n=285).

RESULTS

Overall, 572 patients met eligibility criteria with 2855 patient-years of follow-up. The 5-year cumulative proportion of SCD events was 9.1% (14 SCD, 25 resuscitated sudden cardiac arrests, and 14 aborted SCD). Risk predictors included age at diagnosis, documented nonsustained ventricular tachycardia, unexplained syncope, septal diameter z-score, left ventricular posterior wall diameter z score, left atrial diameter z score, peak left ventricular outflow tract gradient, and presence of a pathogenic variant. Unlike in adults, left ventricular outflow tract gradient had an inverse association, and family history of SCD had no association with SCD. Clinical and clinical/genetic models were developed to predict 5-year freedom from SCD. Both models adequately discriminated between patients with and without SCD events with a c-statistic of 0.75 and 0.76, respectively, and demonstrated good agreement between predicted and observed events in the primary and validation cohorts (validation c-statistic 0.71 and 0.72, respectively).

CONCLUSION

Our study provides a validated SCD risk prediction model with >70% prediction accuracy and incorporates risk factors that are unique to pediatric hypertrophic cardiomyopathy. An individualized risk prediction model has the potential to improve the application of clinical practice guidelines and shared decision making for implantable cardioverter defibrillator insertion. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT0403679.