A Readmission Risk Prediction Model for Elderly Patients with Coronary Heart Disease

Abstract

Objective: To analyze the independent risk factors and establish a risk prediction model by investigating the readmission of elderly patients with coronary heart disease (CHD) within 1 year after discharge. Methods: A total of 480 CHD patients, who were hospitalized in the Affiliated Hospital of Hebei University from October 2019 to December 2020, were included in this study. A general data scale, mental health status scale, the Clinical Frailty Scale, Pittsburgh Sleep Quality Index, as well as the Family Adaptability and Cohesion Evaluation Scale were used to collect data. According to the number of readmissions due to CHD within 1 year after discharge, the patients were divided into two groups: the readmission group (n = 212) and the no readmission group (n = 268). General data, laboratory examination indicators, frailty, mental health status, sleep status, as well as family intimacy and adaptability were compared between the two groups. Logistic regression was used to analyze the independent risk factors for the readmission of these patients, and R software was used to construct a line diagram model for predicting readmission of elderly patients with CHD. Results: Five factors including body mass index (OR = 1.045), low density lipoprotein (OR = 1.123), frailty (OR = 1.946), mental health (OR = 1.099), as well as family intimacy and adaptability (OR = 0.928) were included to construct the risk prediction model for the readmission of elderly patients with CHD within 1 year after discharge. The ROC curve showed that the area under the curve for predicting readmission of elderly patients with CHD was 0.816; Hosmer-Lemeshow goodness of fit test showed X² = 1.456 and P = 0.989; the maximum Youden index corresponding to the predicted value of risk was 0.526. The results showed that the model could accurately predict the risk of readmission in elderly patients with CHD within 1 year after discharge. Conclusion: This study constructed a line diagram model based on five independent risk factors of the readmission of elderly patients with CHD: body mass index, low density lipoprotein, frailty, mental health status, as well as family intimacy and adaptability. This model has good discrimination, accuracy, and predictive efficiency, providing reference for the early prevention and intervention of readmission in elderly patients with CHD recurrence.