What is the clinical evidence from this study?

Study design: Cohort. Population: Hypertrophic cardiomyopathy (n=314). Intervention: Clinical nomogram (age, smoking, BNP, LVOTO). Primary outcome: Early left ventricular systolic dysfunction progression (ELVSDP) (C-index 0.94, 95% CI 0.92-0.96).

What does this research mean for the field?

A newly developed predictive nomogram incorporating age, smoking history, BNP level, and left ventricular outflow tract obstruction accurately predicts the 6- to 18-month risk of early left ventricular systolic dysfunction progression in patients with hypertrophic cardiomyopathy. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

June 12, 2026Frontiers in Cardiovascular Medicine0 citationsOpen Access

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

YLYu LiHuazhong University of Science and Technology ZDZiqi DuanWuhan Sixth Hospital LJLi JinleiCentral Hospital of Wuhan

Key Result

A clinical nomogram incorporating age, smoking history, BNP level, and left ventricular outflow tract obstruction accurately predicted the short-term risk of early left ventricular systolic dysfunction progression in hypertrophic cardiomyopathy, with a C-index of 0.94.

Study Design

Type

Cohort (n=314)

Multicenter

Structured PICO

Can a nomogram based on clinical and echocardiographic parameters accurately predict the short-term risk of early left ventricular systolic dysfunction progression in patients with hypertrophic cardiomyopathy?

Population

314 adults with hypertrophic cardiomyopathy and preserved left ventricular ejection fraction at baseline, followed for a median of 18.8 months to develop and validate a risk prediction model for early systolic dysfunction progression.

Outcome

Early left ventricular systolic dysfunction progression (ELVSDP) defined as HF with LVEF ≤40%, absolute decline in LVEF from ≥50% at baseline to ≤50%, or relative decline in LVEF ≥10% from baseline with clinical signs or symptoms of HF, assessed at 6, 12, and 18 months.composite

A nomogram incorporating age, smoking history, BNP, and LVOTO accurately predicts the short-term risk of early left ventricular systolic dysfunction progression in patients with hypertrophic cardiomyopathy.

Main Result

Effect estimate: C-index 0.94 (95% CI 0.92-0.96)

Limitations

Retrospective analysis from a single center.
Validation set originates from the same institution (internal validation only), which may lead to optimistic performance estimates.
Older population with a high burden of comorbidities, limiting generalizability to younger or asymptomatic patients.
Did not include advanced imaging techniques (e.g., late gadolinium enhancement) or genetic markers.
Linear Cox model cannot capture potential nonlinear relationships between baseline LVEF and ELVSDP risk.
Composite endpoint definition includes subjective symptoms and depends on echocardiographic variability.
Cannot distinguish whether ELVSDP progression is primarily driven by comorbidities or HCM-specific evolution.

Abstract

Background 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. Methods 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. Results 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). Conclusion The nomogram developed in this study accurately predicts short-term ELVSDP risk in HCM patients, facilitating early risk stratification and individualized management. Clinical Trial Registration This study was registered at the Chinese Clinical Trial Registry http://www.chictr.org.cn/ , registration number ChiCTR2500106648 Registration Date: 2025-07-28.

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