The Novel HyperHF risk model using left atrial volume index predicted cardio-cerebral events in hypertrophic cardiomyopathy with the highest accuracy among tested models (AUC 0.717, p<0.001).
Cohort (n=295)
Does the Novel HyperHF risk model improve prediction of cardio-cerebral events in patients with hypertrophic cardiomyopathy compared to the conventional HCM Risk-SCD model?
A novel CPET-derived HyperHF score using left atrial volume index provides better prediction of cardio-cerebral events in hypertrophic cardiomyopathy patients than the conventional HCM Risk-SCD score.
Estimación del efecto: AUC 0.717
valor p: p=<0.001
BACKGROUND: Sudden cardiac death (SCD) and stroke-related events accompanied by atrial fibrillation (AF) can affect morbidity and mortality in hypertrophic cardiomyopathy (HCM). This study sought to evaluate a scoring system predicting cardio-cerebral events in HCM patients using cardiopulmonary exercise testing (CPET). METHODS: We investigated the role of a previous prediction model based on CPET, the HYPertrophic Exercise-derived Risk score for Heart Failure-related events (HyperHF), which is derived from peak circulatory power ventilatory efficiency and left atrial diameter (LAD), for predicting a composite of SCD-related (SCD, serious ventricular arrhythmia, death from cardiac cause, heart failure admission) and stroke-related (new-onset AF, acute stroke) events. The Novel HyperHF risk model using left atrial volume index (LAVI) instead of LAD was proposed and compared with the previous HCM Risk-SCD model. RESULTS: A total of 295 consecutive HCM patients (age 59.9±13.2, 71.2% male) who underwent CPET was included in the present study. During a median follow-up of 742 days (interquartile range 384-1047 days), 29 patients (9.8%) experienced an event (SCD-related event: 14 patients (4.7%); stroke-related event: 17 patients (5.8%)). The previous model for SCD risk score showed fair prediction ability (AUC of HCM Risk-SCD 0.670, p = 0.002; AUC of HyperHF 0.691, p = 0.001). However, the prediction power of Novel HyperHF showed the highest value among the models (AUC of Novel HyperHF 0.717, p<0.001). CONCLUSIONS: Both conventional HCM Risk-SCD score and CPET-derived HyperHF score were useful for prediction of overall risk of SCD-related and stroke-related events in HCM. Novel HyperHF score using LAVI could be utilized for a better prediction power.
Lee et al. (Fri,) conducted a cohort in Hypertrophic cardiomyopathy (n=295). Novel HyperHF risk model vs. HCM Risk-SCD model was evaluated on Composite of SCD-related (SCD, serious ventricular arrhythmia, death from cardiac cause, heart failure admission) and stroke-related (new-onset AF, acute stroke) events (AUC 0.717, p=<0.001). The Novel HyperHF risk model using left atrial volume index predicted cardio-cerebral events in hypertrophic cardiomyopathy with the highest accuracy among tested models (AUC 0.717, p<0.001).