Effect of a Lifestyle-Focused Web-Based Application on Risk Factor Management in Patients Who Have Had a Myocardial Infarction: Randomized Controlled Trial

Abstract

Background: Cardiac rehabilitation is central in reducing mortality and morbidity after myocardial infarction. However, the fulfillment of guideline-recommended cardiac rehabilitation targets is unsatisfactory. eHealth offers new possibilities to improve clinical care.

Objective: This study aims to assess the effect of a web-based application designed to support adherence to lifestyle advice and self-control of risk factors (intervention) in addition to center-based cardiac rehabilitation, compared with cardiac rehabilitation only (usual care).

Methods: All 150 patients participated in cardiac rehabilitation. Patients randomized to the intervention group (n=101) received access to the application for 25 weeks where information about lifestyle (eg, diet and physical activity), risk factors (eg, weight and blood pressure [BP]), and symptoms could be registered. The software provided feedback and lifestyle advice. The primary outcome was a change in submaximal exercise capacity (Watts [W]) between follow-up visits. Secondary outcomes included changes in modifiable risk factors between baseline and follow-up visits and uptake and adherence to the application. Regression analysis was used, adjusting for relevant baseline variables.

Results: There was a nonsignificant trend toward a larger change in exercise capacity in the intervention group (n=66) compared with the usual care group (n=40; +14.4, SD 19.0 W, vs +10.3, SD 16.1 W; P=.22). Patients in the intervention group achieved significantly larger BP reduction compared with usual care patients at 2 weeks (systolic -27.7 vs -16.4 mm Hg; P=.006) and at 6 to 10 weeks (systolic -25.3 vs -16.4 mm Hg; P=.02, and diastolic -13.4 vs -9.1 mm Hg; P=.05). A healthy diet index score improved significantly more between baseline and the 2-week follow-up in the intervention group (+2.3 vs +1.4 points; P=.05), mostly owing to an increase in the consumption of fish and fruit. At 6 to 10 weeks, 64% (14/22) versus 46% (5/11) of smokers in the intervention versus usual care groups had quit smoking, and at 12 to 14 months, the respective percentages were 55% (12/22) versus 36% (4/11). However, the number of smokers in the study was low (33/149, 21.9%), and the differences were nonsignificant. Attendance in cardiac rehabilitation was high, with 96% (96/100) of patients in the intervention group and 98% (48/49) of patients receiving usual care only attending 12- to 14-month follow-up. Uptake (logging data in the application at least once) was 86.1% (87/101). Adherence (logging data at least twice weekly) was 91% (79/87) in week 1 and 56% (49/87) in week 25.

Conclusions: Complementing cardiac rehabilitation with a web-based application improved BP and dietary habits during the first months after myocardial infarction. A nonsignificant tendency toward better exercise capacity and higher smoking cessation rates was observed. Although the study group was small, these positive trends support further development of eHealth in cardiac rehabilitation.

Trial registration: ClinicalTrials.gov NCT03260582; https://ichgcp.net/clinical-trials-registry/NCT03260582.

International registered report identifier (irrid): RR2-10.1186/s13063-018-3118-1.

Keywords: cardiac rehabilitation; cardiovascular; eHealth; mobile device app; mobile phone; risk factors; web-based application.

Conflict of interest statement

Conflicts of Interest: None declared.

©Halldóra Ögmundsdóttir Michelsen, Ingela Sjölin, Maria Bäck, Manuel Gonzalez Garcia, Anneli Olsson, Camilla Sandberg, Alexandru Schiopu, Margrét Leósdóttir. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.03.2022.

Figures

Figure 1

The follow-up of the patients who have had a myocardial infarction, in the study.

Figure 2

Screenshots of the LifePod patient interface (top) and medical interface (bottom). The software could be accessed through a smartphone, tablet, or computer.

Figure 3

A flowchart displaying the recruitment process and flow of participants in the usual care and intervention groups.

Figure 4

A boxplot of the change in submaximal exercise capacity in the intervention group and the usual care group. The difference in change in exercise capacity among the groups was nonsignificant.

Figure 5

Decrease in systolic and diastolic blood pressure between baseline and follow-up visits (absolute values). P values are adjusted for gender, age, weight, previous coronary heart disease, and smoking status at the time of the index event.

Figure 6

Percentage of patients logging data to the web-based application at least twice weekly.