Abstract
BACKGROUND: Although great progress has been made in caring for patients with acute coronary syndrome (ACS), the incidence of heart failure (HF) after discharge remains high after ACS. AIMS: We aimed to investigate the risk predictors for new-onset HF and build a simple nomogram to optimize the clinical management of female patients. METHODS: The clinical data of 319 female patients with ACS between January 1, 2021 and January 1, 2022, were obtained from the Zhejiang Provincial People's Hospital. Multivariate logistic regression analysis was carried out to build the prediction model among all participants and then verified by 10-fold cross-validation. The discrimination, calibration, and clinical usefulness of the prediction model were assessed using receiver operating characteristic curve, calibration curve, and decision curve analyses. RESULTS: This study analyzed 15 potential independent risk predictors of new-onset HF in 319 female patients with ACS. The incidence of HF onset was 23.2%. The following 5 independent risk predictors were filtered out as most relevant for predicting 12-month HF onset: left ventricular ejection fraction ≤ 60.5%, high-density lipoprotein ≤ 1.055 mmol/L, human epididymal protein 4 > 69.6 pmol/L, creatinine > 71.95 µmol/L, and diagnosis of myocardial infarction (MI). CONCLUSION: Our nomogram, which used five easily obtained clinical variables, could be a useful tool to help identify female individuals with ACS who are at high risk of developing HF after discharge and facilitate communication between female patients and physicians.