Evidence map›Paper›PMID 40671941›Full record

ArticlePatient preference and adherence2025

Factors Influencing Cardiac Rehabilitation Compliance in Elderly Myocardial Infarction Patients and the Development of a Nomogram Prediction Model.

Baihua Zhou, Jun Yan, Qin Wang, Qiwei He, Wei Ao, Ying Yang, Yanjiao Ren

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Article in Patient preference and adherence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Baihua ZhouDepartment of Cardiovascular Medicine, Yueyang People's Hospital, Yueyang, Hunan, 414000, People's Republic of China.
Jun YanDepartment of Cardiovascular Medicine, Yueyang People's Hospital, Yueyang, Hunan, 414000, People's Republic of China.
Qin WangDepartment of Cardiovascular Medicine, Yueyang People's Hospital, Yueyang, Hunan, 414000, People's Republic of China.
Qiwei HeDepartment of Cardiovascular Medicine, Yueyang People's Hospital, Yueyang, Hunan, 414000, People's Republic of China.
Wei AoDepartment of Cardiovascular Medicine, Yueyang People's Hospital, Yueyang, Hunan, 414000, People's Republic of China.
Ying YangDepartment of Cardiovascular Medicine, Yueyang People's Hospital, Yueyang, Hunan, 414000, People's Republic of China.
Yanjiao RenDepartment of Cardiovascular Medicine, Yueyang People's Hospital, Yueyang, Hunan, 414000, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 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.

Indexed as

cardiac rehabilitationcomplianceinfluencing factorsmyocardial infarctionnomogram

Identifiers

PMID40671941
PMCPMC12264351

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