Effects of a Home-Based Rehabilitation Exercise Program on Cardiorespiratory Performance in Community-Dwelling Adults Who Underwent Heart Surgery: Randomized Controlled Trial
Bibliographic record
Abstract
Background: Patients undergoing heart surgery demonstrate impaired cardiorespiratory performance. Phase II cardiac rehabilitation (CR) in people undergoing open heart surgery (OHS) aims to reduce the adverse physical effects of cardiovascular diseases. Virtual reality (VR) exercise is now used in CR. Objective: This study aimed to explore the effects of VR exercise on functional capacity, pulmonary function, and respiratory muscle strength in patients who underwent OHS and were in phase II CR. Methods: Forty-nine patients who underwent elective OHS and were in phase II CR were randomized into a VR group (N=24) and a control group (N=25). The VR group completed 8 weeks of a home-based VR exercise program, including chest trunk mobilization and aerobic circuit training for 30 minutes, whereas the control group received an exercise brochure and information regarding the benefits of exercise. Intention-to-treat analysis was conducted, and 2-way mixed ANOVA was performed to compare between- and within-group differences in functional capacity and respiratory performance. Results: After completing the 8-week program, the VR group showed significant improvement in functional capacity compared to the control group (66.29, SD 25.84 m; P=.01). Inspiratory muscle strength increased in both the VR and control groups compared to baseline (9.46, SD 2.85 and 9.64, SD 2.78 cm H2O, respectively). In addition, after the 8-week intervention, significant improvements were found in expiratory muscle strength (15.79, SD 4.65 cm H2O) and forced expiratory volume in 1 second as a percentage of predicted values (2.96%, SD 1.52%) in the VR group compared to the baseline session. Conclusions: The home-based VR exercise program significantly improved functional capacity but not respiratory muscle or pulmonary function.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".