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影响老年心肌梗死患者心脏康复依从性的因素及诺模图预测模型的构建
Authors Zhou B, Yan J, Wang Q, He Q, Ao W, Yang Y, Ren Y
Received 21 March 2025
Accepted for publication 7 July 2025
Published 11 July 2025 Volume 2025:19 Pages 2015—2025
DOI https://doi.org/10.2147/PPA.S529753
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Jongwha Chang
Baihua Zhou, Jun Yan, Qin Wang, Qiwei He, Wei Ao, Ying Yang, Yanjiao Ren
Department of Cardiovascular Medicine, Yueyang People’s Hospital, Yueyang, Hunan, 414000, People’s Republic of China
Correspondence: Yanjiao Ren, Department of Cardiovascular Medicine, Yueyang People’s Hospital, No. 263, Baling East Road, Yueyang Lou District, Yueyang, Hunan, 414000, People’s Republic of China, Tel +8613902405429, Email a18711179119@126.com
Objective: To explore the influencing factors of cardiac rehabilitation compliance in elderly patients with acute myocardial infarction (AMI) and to construct a nomogram prediction model.
Methods: A retrospective study was conducted on 239 elderly AMI patients admitted to our hospital from April 2022 to April 2024. The patients were randomly assigned into a modeling group (167 cases) and a validation group (72 cases) in a 7:3 ratio. The modeling group was separated into a good compliance group and a poor compliance group based on their compliance with cardiac rehabilitation.
Results: Among the 167 patients in the modeling group, 67 had poor compliance, with an incidence rate of 40.12%. Multivariate logistic regression revealed that age, educational level, perception of disease, anxiety and depression, social support, and medical staff supervision were risk factors for cardiac rehabilitation compliance in elderly AMI patients (P< 0.05). The AUC values of the modeling and validation groups were 0.955 and 0.937, respectively. The slope of the calibration curve was close to 1, and the H-L test showed χ2=7.863 and 7.453, with P=0.789 and 0.775, indicating good consistency. DCA curve showed that when the high-risk threshold probability was between 0.08 and 0.93, the nomogram model had a high clinical value.
Conclusion: Age, educational level, perception of the disease, anxiety and depression, social support, and medical staff supervision are the influencing factors of cardiac rehabilitation compliance in elderly AMI patients. The nomogram model constructed based on this has good discrimination and consistency, and can predict cardiac rehabilitation compliance.
Keywords: myocardial infarction, cardiac rehabilitation, compliance, influencing factors, nomogram