Construction of a risk prediction model for moderate to severe heart failure in elderly inpatients with chronic heart failure
Objective To construct a risk prediction model for moderate to severe heart failure in patients with chronic heart failure(CHF)based on electronic medical records,and verify the predictive effect of the model.Methods A total of 299 patients diagnosed with CHF in cardiovascular clinical medical center of a grade Ⅲ-A hospital in Shanghai from January 2019 to December 2020 were selected as the research subjects.Logistic regression was used to establish the risk prediction mod-el for moderate to severe heart failure in CHF patients.Hosmer-Lemeshow and receiver operating characteristic curve(ROC)were used to test the goodness of fit and prediction effect of the model,respectively.A total of 100 patients were enrolled to verify the model.Results Cardiac ultrasound(reduced motion amplitude)(OR = 5.109),edema of both lower limbs(OR =3.947),atrial fibrillation(OR =2.772),and elevated serum creatinine(OR =1.015)were risk factorsfor moderate to severe heart failure in patients with CHF,while elevated serum albumin(OR =0.939)was a protective factor.Hosmer-Leme-show test showed that P =0.127,the area under the ROC curve was0.858,the Youden index was0.528,the optimal critical value was 0.805,the sensitivity was 0.731,the specificity was 0.797,and the accuracy of practical application was 77.00%.Conclusion The predictive model established in this study for the risk of moderate to severe heart failure in CHF patients ex-hibits good predictive performance,which is beneficial for the early identification of the risk of moderate to severe heart failure in the future,and provides a basis for updating the electronic system alarm program.
electronic medical recordchronic heart failuremoderate to severerisk prediction modelnursing
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