A predictive model for heart failure in patients with hypertension and persistent atrial fibrillation: A retrospective single-center study

OBJECTIVE: This study aimed to develop and validate a predictive nomogram for heart failure in patients with hypertension and persistent atrial fibrillation (HT-PeAF). METHODS: We retrospectively analyzed clinical data from patients with HT-PeAF hospitalized at Chinese People's Liberation Army General Hospital between 2010 and 2019. Predictive variables were selected based on multivariable logistic regression analysis and clinical relevance, which were then incorporated into a clinical nomogram. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) for discrimination, the Hosmer-Lemeshow test for calibration, and decision curve analysis for clinical utility. RESULTS: Of the 395 enrolled patients, 151 experienced heart failure. Nine predictive variables were identified: prior catheter ablation, low-density lipoprotein cholesterol, hemoglobin, uric acid, creatinine, total bilirubin, fasting blood glucose, red blood cell distribution width, and coronary artery disease. The nomogram demonstrated good discriminative ability (AUC = 0.77, 95% CI: 0.72-0.81), good calibration (P = 0.44), and favorable clinical utility. CONCLUSION: This accessible tool facilitates individualized risk stratification for heart failure in HT-PeAF patients, though prospective validation in multicenter Asian cohorts is warranted.