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A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
Published on: April 19, 2019
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Factors that predict compliance in a virtual cardiac rehabilitation program
Natalie Z M Eichner1, Qiuyu Martin Zhu2, Adelita Granados3
1Penn State College of Medicine, Hershey, PA 17033, USA.
International Journal of Cardiology
|September 18, 2023
Summary
Younger age, diabetes, and smoking predict lower attendance in virtual cardiac rehabilitation (CR). Interventions can target these factors to improve CR program participation for cardiovascular disease patients.
Area of Science:
- Cardiology
- Digital Health
- Public Health
Background:
- Cardiac rehabilitation (CR) offers significant benefits for cardiovascular disease (CVD) patients, yet participation rates remain suboptimal.
- Virtual CR programs offer a scalable solution to increase access and utilization.
- Limited data exists on compliance factors within large-scale virtual CR programs.
Purpose of the Study:
- To identify predictors of compliance in a large virtual CR program.
- To inform targeted interventions for improving CR utilization.
Main Methods:
- Analysis of 1409 patients in a US-based virtual CR program (12 telephone sessions).
- Collected demographic data, clinical factors (weight, BP, HbA1c, smoking), and CVD diagnoses.
- Compliance defined as ≥75% attendance; analyzed using regression models (P < 0.05).
Main Results:
- Younger age was the strongest predictor of non-compliance.
- HbA1c level, CVD diagnoses, and smoking status also moderately predicted compliance.
- Combining smoking and HbA1c significantly improved prediction (R²=0.79).
Conclusions:
- Age, diabetes, CVD diagnoses, and smoking status are key independent predictors of virtual CR compliance.
- Findings support developing targeted interventions to enhance CR program adherence.
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