Clin Res Cardiol (2023). https://doi.org/10.1007/s00392-023-02180-w

Maintenance in cardiovascular rehabilitation: a systematic review and meta-analysis of eHealth interventions
M. Heimer1, S. Schmitz2, M. Teschler3, H. Schäfer1, F. Mooren1, T. Meyer4, M. Habibovic5, E. R. Douma5, W. Kop5, B. Schmitz3
1Fakultät für Gesundheit, Lehrstuhl für Rehabilitationswissenschaften, Fakultät für Gesundheit, Universität Witten/Herdecke, Witten; 2Fakultät für Gesundheitswissenschaften, Universität Bielefeld, Bielefeld; 3Zentrum für Rehabilitation, Klinik Königsfeld, Ennepetal; 4Institut für Rehabilitationsmedizin, Martin-Luther-Universität Halle-Wittenberg, Halle; 5Department of Medical and Clinical Psychology, Tilburg University, Tilburg, NL;

Background: Cardiac rehabilitation (CR) is effective to decrease the morbidity and mortality risk in coronary artery disease (CAD) patients. Despite solid evidence of the effectiveness of structured phase II CR performed as either inpatient, outpatient, or homebased programs, adherence to a healthy lifestyle including regular physical activity (PA) and risk factor management during subsequent phase III CR maintenance is still challenging and poorly supported. eHealth-based maintenance solutions have been suggested to overcome this gap in patient care. However, the efficacy of eHealth for maintenance CR in CAD on risk factors and adherence to a healthy lifestyle are still a matter of debate.
Methods: To analyze the effects of eHealth in phase III CR on behavioral, health-related, and clinical outcomes a systematic review (PROSPERO, CRD42020203578) of the literature was conducted (PubMed, CINAHL, MEDLINE, Web of Science). A meta-analysis with outcome-oriented overall effect estimates was conducted following the Cochrane Collaboration guidelines using Review Manager (RevMan5.4). Effects were analyzed using the inverse variance in a random-effect model for continuous, and the Mantel-Haenszel method in a fixed-model for dichotomous data. Any original article published until May 2022 reporting on eHealth in phase III CR was considered for the analysis. Only articles reporting on CAD patients that underwent a structured center-based inpatient or outpatient phase II CR were included. Articles had to be Randomized Controlled Trials (quasi-experimental design was also acceptable). Only studies with N ≥ 30 patients at baseline were included. Analyses were conducted on short-term (≤ 6 months) and medium/long-term effects (> 6 months). Behavioral change techniques (BCTs) were defined based on the described intervention and coded according to the BCT handbook.

Results: Fourteen studies with 1.497 patients were included. eHealth significantly promoted PA including exercise and daily activity (steps) (SMD=0.35; 95% CI 0.02 to 0.70; p=0.04; I2=82.3%; n=957) as well as exercise capacity (SMD=0.29; 95% CI 0.05 to 0.52; p=0.02; I2=0.0%; n=282), after 6 months compared to usual care. Quality of life (QoL) was higher with eHealth ≤ 6 months in phase III CR (SMD=0.17; 95% CI 0.02 to 0.32; p=0.02; I2=0.0%; n=688). Systolic blood pressure decreased after 6 months with eHealth compared to care as usual (SMD=-0.20; 95%CI -0.40 – 0,00; p=0.046). No effects on BMI, total and low-density lipoprotein cholesterol, mental health, and rehospitalization were detected. Studies showed great heterogeneity in the adapted BCTs and type of intervention. Mapping of BCTs revealed that self-monitoring of behavior and/or goal setting, as well as feedback on behavior were most frequently included. Reported behavioral change theories involved the Health Action Process Approach (HAPA), I-Change Model and social cognitive theory.

Conclusions: eHealth in phase III CR may be applied for maintenance of behavioral change in CAD patients since it effectively improves PA and exercise capacity, while increasing short-term QoL and decreasing systolic blood pressure. Data of eHealth effects on mortality, morbidity, and clinical outcomes is scarce, and should be provided by future studies.

 


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