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Previous data have validated the benefit of digital health interventions (DHIs) on weight loss in patients following acute coronary syndrome entering cardiac rehabilitation (CR).
The primary purpose of this study was to test the hypothesis that increased DHI use, as measured by individual log-ins, is associated with improved weight loss. Secondary analyses evaluated the association between log-ins and activity within the platform and exercise, dietary, and medication adherence.
We obtained DHI data including active days, total log-ins, tasks completed, educational modules reviewed, medication adherence, and nonmonetary incentive points earned in patients undergoing standard CR following acute coronary syndrome. Linear regression followed by multivariable models were used to evaluate associations between DHI log-ins and weight loss or dietary adherence.
Participants (n=61) were 79% male (48/61) with mean age of 61.0 (SD 9.7) years. We found a significant positive association of total log-ins during CR with weight loss (
These data extend our previous findings and demonstrate increased DHI log-ins portend improved weight loss in patients undergoing CR after acute coronary syndrome. DHI adherence can potentially be monitored and used as a tool to selectively encourage patients to adhere to secondary prevention lifestyle modifications.
ClinicalTrials.gov (NCT01883050); https://clinicaltrials.gov/ct2/show/NCT01883050
Cardiovascular disease (CVD) is the primary cause for morbidity, mortality, and rising health care–associated costs in the United States [
In addition to meta-analytic data demonstrating improved CVD outcomes with digital health intervention (DHI) participation [
Patient data was abstracted from a combination of a feasibility study (n=24) [
CONSORT diagram for digital health use substudy of initial feasibility study and randomized trial.
The DHI has been previously described [
Baseline and 3-month assessments included standard laboratory blood tests for fasting lipid panels and serum glucose values. These data were obtained from the Mayo Clinic cardiovascular health clinic database by a blinded abstractor and underwent statistical review by a blinded statistician. Furthermore, CR staff collected CR data blinded to the group allocation. Most patients in the study group underwent exercise stress testing at baseline and after 3 months per clinical protocol. The patients’ CR providers assessed end points such as blood pressure, height, weight, and the health behavior questionnaires (including diet, physical activity, Dartmouth QOL Index, stress, and smoking status) at baseline and after 3 months in standard fashion. Weight and blood pressure were measured at every CR visit in standard fashion, with weight being assessed with clothes on and shoes off, and blood pressure assessed by BpTRU (BpTRU Medical Devices). Stress scores were answered on a 1 to 10 scale [
Deidentified data were transmitted through Healarium (Healarium Inc) to the investigators for a comprehensive data analysis at the completion of the program. Patient-provided data in the DHI group were collected but not used in the analysis comparing the two groups. Patients who did not initially report for their intake into CR were removed from the analysis as primary and secondary outcomes data could not be assessed and verified.
DHI data were also assembled and transferred in a deidentified manner and included total log-ins, days logged in, educational modules viewed, and tasks completed in total and broken down by subtasks (weight, exercise, blood pressure, glucose, and medications). We also abstracted and analyzed data for nonmonetary-based incentive markers called Healthies, incentive points given to patients after they completed tasks and milestones such as logging in or reaching certain targets for weight, blood pressure, etc. Values for point allotments were prespecified.
Continuous variables were summarized as mean and standard deviation; categorical variables as frequency and percentage. Group comparisons were made using Student
Baseline demographics revealed similar baseline statistics between both groups (
Baseline demographics of participants.
Characteristics | RCTa n=37 | Feasibility n=24 | ||
Age in years, mean (SD) | 62.5 (10.7) | 60.1 (12.4) | .69 | |
Gender, male, n (%) | 30 (81) | 18 (75) | .43 | |
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Working | 21 (57) | 12 (50) | — |
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Retired/disabled | 16 (43) | 10 (42) | — |
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Professional | 12 (34) | 5 (21) | — |
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Skilled labor | 13 (37) | 11 (46) | — |
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Unskilled labor | 5 (14) | 4 (17) | — |
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White collar | 5 (14) | 4 (17) | — |
Married, n (%) | 32 (87) | 17 (71) | .29 | |
Education in years, mean (SD) | 14.7 (2.1) | 14.4 (2.1) | .50 | |
Metabolic syndrome, n (%) | 16 (44) | 8 (33) | .34 | |
Diabetes, n (%) | 11 (32) | 6 (26) | .73 | |
Hyperlipidemia, n (%) | 33 (89) | 22 (96) | .79 | |
Hypertension, n (%) | 28 (82) | 16 (70) | .29 | |
Family history of CVDa, n (%) | 26 (70) | 14 (55) | .65 | |
Current tobacco, n (%) | 1 (3) | 3 (14) | .24 | |
Weight (kg), mean (SD) | 95.8 (19.8) | 93.7 (19.8) | .70 | |
Systolic blood pressure (mm Hg), mean (SD) | 118.4 (15.9) | 124.3 (14.7) | .16 | |
Glucose (mg/dL), mean (SD) | 122.3 (45.9) | 123.5 (38.5) | .92 |
aRCT: randomized controlled trial.
bCVD: cardiovascular disease.
There was a significant association of total log-ins during CR with weight loss (
Weight loss (kg) compared with number of log-ins during the 3-month cardiac rehabilitation period (
Number of log-ins during 3 months of cardiac rehabilitation compared with (A) diet scores (
Similarly, there was a significant correlation between Healthies and weight loss (
Increased collection of Healthies, nonmonetary point-based incentives, was significantly associated with (A) improved weight loss and (B) improvements in Dartmouth Quality of Life.
Educational modules viewed (
Increased weight loss was associated with (A) an increased number of digital health tasks completed (
In this study, we have demonstrated that there is a significant association between total log-ins and weight loss in patients in CR assigned to a DHI. These data support the notion of a dose-dependent effect of a DHI on weight loss and extend our previous work highlighting the success of a DHI in improving weight loss for both primary and secondary prevention [
Despite the growing prevalence of digital/mobile health tools in health care with more than 100,000 medically related apps available for download, there are sparse data to show an overall benefit let alone promise of a dose-dependent effect of DHIs. There are data supporting the notions that increased follow-up frequency improves weight loss in a bariatric surgery population [
Our study is congruent with prior subanalyses showing that improved DHI use equates with improved target attainment and intentions toward behavior change [
Despite the positive overall message supporting a dose-dependent effect of a DHI on weight loss, there are a few limitations in this study. Notably, this is a willing convenience sample comprising a feasibility/pilot study and the subsequent RCT. However, there were not substantial changes to the protocols among the two sections of the overall project, and the baseline demographics are similar. Another limitation is the lack of standardization on how to quantify use in the digital/mobile community. This has been previously studied in a systematic review which elegantly details that justifications for use are usually lacking in the assessment of DHI adherence [
We are able to demonstrate a use-dependent effect of DHIs on secondary prevention with regard to weight loss in patients participating in standard CR. Adherence metrics should be recorded and reported in mobile/digital health trials, and further work should be done to elucidate the most appropriate use metrics in these trials. Furthermore, these data support the notion that increased contact with patients through mobile/digital mechanisms can have additive benefits in terms of improved body weight profiles.
cardiovascular disease
cardiac rehabilitation
digital health intervention
percutaneous coronary intervention
quality of life
randomized controlled trial
root mean squared error
South Asian Heart Risk Assessment
We would like to thank the Binational Industrial Research and Development (BIRD) Foundation for their generous support for this project. The BIRD Foundation had no role in the design, execution, or publication of these data.
None declared.