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. 2025 Jul 11:19:2015-2025.
doi: 10.2147/PPA.S529753. eCollection 2025.

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

Baihua Zhou  1 , Jun Yan  1 , Qin Wang  1 , Qiwei He  1 , Wei Ao  1 , Ying Yang  1 , Yanjiao Ren  1
Affiliations

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

Baihua Zhou et al. Patient Prefer Adherence. .

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 χ 2=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: cardiac rehabilitation; compliance; influencing factors; myocardial infarction; nomogram.

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Conflict of interest statement

All authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Flow chart of case collection.
Figure 2
Figure 2
Development of a nomogram modelling of adherence to cardiac rehabilitation in elderly patients with AMI.
Figure 3
Figure 3
Nomogram Model of the Modeling Group, (A) ROC curve for modelling group; (B) Modelling group calibration curves.
Figure 4
Figure 4
Nomogram Model of the Validation Group, (A) ROC curve for the validation group; (B) Calibration curve for the validation group.
Figure 5
Figure 5
DCA curve for the nomogram.
See this image and copyright information in PMC

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