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Record W4401634738 · doi:10.2196/59098

A Dual-Modality Home-Based Cardiac Rehabilitation Program for Adults With Cardiovascular Disease: Single-Arm Remote Clinical Trial

2024· article· en· W4401634738 on OpenAlexvenueno aff
Tim Bilbrey, Jenny Martin, Wen Zhou, Changhao Bai, Nitin Vaswani, Rishab Shah, Sara Chokshi, Xi Chen, Satjit Bhusri, Hongdao Meng, Zhen Lei

Bibliographic record

VenueJMIR mhealth and uhealth · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintMedicineRehabilitationModality (human–computer interaction)Physical medicine and rehabilitationPhysical therapyDiseaseComputer scienceInternal medicineHuman–computer interactionWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Cardiac rehabilitation (CR) is a safe, effective intervention for individuals with cardiovascular disease (CVD). However, a majority of eligible patients do not complete CR. Growing evidence suggests that home-based cardiac rehabilitation (HBCR) programs are comparable in effectiveness and safety with traditional center-based programs. More research is needed to explore different ways to deliver HBCR programs to patients with CVD. OBJECTIVE: We aimed to assess the feasibility and impact of a digital HBCR program (RecoveryPlus.Health) that integrates both telehealth and mHealth modalities on functional exercise capacity, resting heart rate, and quality of life among adults with CVD. METHODS: This 12-week prospective, single-arm remote clinical trial used a within-subject design. We recruited adults with CVD (aged ≥40 years) from the community with a CR-eligible diagnosis (stable angina pectoris, myocardial infarction, and heart failure) between May and August 2023. All enrolled patients referred to the RPH clinic in Roanoke, Texas, were included. The care team provided guideline-concordant CR services to study participants via two modalities: (1) a synchronous telehealth exercise training through videoconferencing; and (2) an asynchronous mobile health (mHealth) coaching app (RPH app). Baseline intake survey, electronic health record, and app log data were used to extract individual characteristics, care processes, and platform engagement data. Feasibility was measured by program completion rate and CR service use. Efficacy was measured by changes in the 6-minute walk test, resting heart rate, and quality of life (12-Item Short-Form Health Survey) before and after the 12-week program. Paired t tests were used to examine pre- and postintervention changes in the outcome variables. RESULTS: In total, 162 met the inclusion criteria and 75 (46.3%) consented and were enrolled (mean age 64, SD 10.30 years; male: n=37, 49%; White: n=46, 61%). Heart failure was the most common diagnosis (37/75, 49%). In total, 62/75 (83%) participants completed the 12-week study and used the telehealth modality with 9.63 (SD 3.33) sessions completed, and 59/75 (79%) used the mHealth modality with 10.97 (SD 11.70) sessions completed. Post intervention, 50/62 (81%) participants' performance in the 6-minute walk test had improved, with an average improvement of 40 (SD 63.39) m (95% CI 25.6-57.1). The average 12-Item Short-Form Health Survey's physical and mental summary scores improved by 2.7 (SD 6.47) points (95% CI 1.1-4.3) and 2.2 (SD 9.09) points (95% CI 0.1-4.5), respectively. There were no changes in resting heart rate and no exercise-related adverse events were reported. CONCLUSIONS: The RecoveryPlus.Health digital HBCR program showed feasibility and efficacy in a group of nationally recruited patients with CVD. The findings add to the evidence that a telehealth and mHealth dual-modality HBCR program may be a promising approach to overcome some of the main barriers to improving CR access in the United States. TRIAL REGISTRATION: ClinicalTrials.gov NCT05804500; https://clinicaltrials.gov/search?cond=NCT05804500.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.438
Teacher spread0.371 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2024
Admission routes1
Has abstractyes

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