4.6 Article

The impact of cardiopulmonary exercise-derived scoring on prediction of cardio-cerebral outcome in hypertrophic cardiomyopathy

Journal

PLOS ONE
Volume 17, Issue 1, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0259638

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Funding

  1. Bisa Research Grant of Keimyung University

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This study evaluated the ability of a scoring system based on cardiopulmonary exercise testing (CPET) to predict cardio-cerebral events in patients with hypertrophic cardiomyopathy (HCM). The results showed that the novel scoring model using left atrial volume index (LAVI) had the highest predictive power among the models.
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.

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