Prediction model for early left ventricular systolic dysfunction progression in hypertrophic cardiomyopathy

The risk of early left ventricular systolic dysfunction progression (ELVSDP) among patients with hypertrophic cardiomyopathy (HCM) is heterogeneous, and accurate short-and medium-term prediction tools are lacking. This study aimed to develop and validate a predictive model for the risk of ELVSDP in HCM patients at 6, 12, and 18 months.

A total of 314 HCM patients without ELVSDP at baseline were included and randomly divided into training and validation sets. LASSO-Cox regression was employed to select variables and identify independent predictors, based on which a nomogram and an interactive dynamic prediction tool were constructed. Model performance was evaluated using the concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Risk stratification was assessed using the Kaplan-Meier method.

Age [hazard ratio (HR) = 1.17], smoking history (HR = 2.79), B-type natriuretic peptide (BNP) level (HR = 1.002), and left ventricular outflow tract obstruction (HR = 2.24) were independent predictors of ELVSDP. The model demonstrated strong performance in both the training and validation sets. The time-dependent area under the curve (AUC) exceeded 0.88 at 6, 12, and 18 months, with C-indices of 0.94 and 0.93, respectively. Bootstrap validation confirmed model stability. Calibration curves showed good agreement between predicted and observed outcomes, and DCA indicated a net clinical benefit. The incidence of ELVSDP was significantly higher in the high-risk group compared to the low-risk group (P < 0.0001).

The nomogram developed in this study accurately predicts short-term ELVSDP risk in HCM patients, facilitating early risk stratification and individualized management.

This study was registered at the Chinese Clinical Trial Registry http://www.chictr.org.cn/, registration number ChiCTR2500106648 [Registration Date: 2025-07-28].