Objective To explore the risk factors of multiple unplanned admissions in patients with heart failure,and to construct and verify a risk prediction model.Methods A total of 498 patients with heart failure who were admitted to the Department of Cardiology of Nantong Sixth People's Hospital from January 2020 to October 2022 were selected by the convenient sampling method.The risk factors of multiple unplanned admissions were analyzed with logistic regression among 332 patients admitted from January 2020 to June 2021(training set),a risk prediction model was constructed.The prediction model was verified among 166 patients admitted from July 2021 to October 2022(validation set)with ROC curve.Results In training set,75 cases had multiple unplanned admission(22.59％).Logistic regression analysis showed that age＞70 years,history of atrial fibrillation,chronic kidney disease,COPD,NYHA class ≥Ⅲ,Hb＜110 g/L,and polypharmacy were independent risk factors of multiple unplanned hospital admission for heart failure.The area under the ROC curve of the final prediction model was 0.864(95％CI:0.802-0.925),the sensitivity was 90.8％,the specificity was 76.8％,and the maximum Youden index was 0.676.Conclusion The risk prediction model of multiple unplanned admission for heart failure constructed in this study has a good prediction effect,which may be used to identify high-risk patients and to intervene in time.
heart failuremultiple unplanned admissionsrisk factorsprediction model
国家科技期刊平台
NSTL
万方数据
