心力衰竭患者低钾血症风险预测模型的构建及验证OA

Objective To construct and validate a risk prediction model for hypokalemia in patients with heart failure(HF).Methods A retrospective selection of 702 HF patients hospitalized in the Department of Cardiovascular Medicine at the Affiliated Hospital of Zunyi Medical University between January 2019 and December 2023 was conducted to form the modeling set.Additionally,a prospective selection of 234 HF patients hospitalized in the same hospital between January 2024 and August 2024 was made to serve as the external validation set.Medical record data were collected using a self-developed"HF Patient Hypokalemia Risk Factor Questionnaire."Predictors were screened using LASSO combined with multivariate logistic regression analysis to construct a risk prediction model and draw a nomogram.The Bootstrap method was employed for internal validation of the model,while the external validation set was utilized for external validation.The model's performance was evaluated using the area under the receiver operating characteristic curve(AUC),calibration curve,Hosmer-Lemeshow test,and decision curve analysis(DCA).Results A total of five predictors were identified:being female,intravenous furosemide dose＞40 mg/d,use of beta-blockers,baseline serum potassium level,and albumin level.Based on these factors,a nomogram model was constructed.The AUC values of the model in the training set and external validation set were 0.811 and 0.807,respectively,indicating moderate discriminative ability.The calibration curve and Hosmer-Lemeshow test(P＞0.05)both suggested good model fit,and the DCA demonstrated that the model had high clinical utility within a specific threshold range.Conclusion The risk prediction model for hypokalemia in HF patients exhibits good predictive performance and can serve as a basis for the early clinical identification of high-risk patients for hypokalemia and for the implementation of individualized interventions.