Predictive model development for left atrial remodeling in hypertrophic cardiomyopathy

Abstract

Abstract Left atrial structural remodeling is closely linked with the prognosis of patients with hypertrophic cardiomyopathy (HCM). This study aimed to evaluate the clinical characteristics and risk factors associated with left atrial remodeling in HCM and to develop an early prediction model. HCM patients who underwent echocardiography during hospitalized enrolled. Patients with a left atrial diastolic anteroposterior diameter ≥ 40 mm were classified as the remodeling group, while others were assigned to the control group. Logistic regression analysis was employed to identify independent predictors, and a nomogram was constructed for prediction. A total of 1554 patients were enrolled, including 442 patients in the remodeling group. Significant differences in clinical and echocardiographic characteristics were observed between the two groups. Multivariate logistic regression analysis identified the following as independent predictors of left atrial remodeling: prothrombin time (P < 0.001; OR 0.863; 95% CI 0.813–0.915), main pulmonary artery diameter (P < 0.001; OR 0.881; 95% CI 0.852–0.911), left ventricular ejection fraction (P < 0.001; OR 1.057; 95% CI 1.043–1.071), and interventricular septal thickness (P < 0.001; OR 0.937; 95% CI 0.916–0.959). A nomogram prediction model based on these factors demonstrated good discriminatory power, with a receiver operating characteristic curve area of 0.7328 (95% CI 0.7052—0.7603). The model’s calibration showed high accuracy and consistency with actual outcomes, particularly in intermediate probability ranges. Prothrombin time, main pulmonary artery diameter, left ventricular ejection fraction, and interventricular septal thickness were identified as risk factors for left atrial remodeling in HCM patients. The developed nomogram provides a valuable tool for early risk assessment, aiding in the early detection of left atrial remodeling and facilitating optimized treatment strategies to improve patient prognosis.

Keywords

• Hypertrophic cardiomyopathy
• Biomarkers
• Left atrial structural remodeling
• Prediction model