Improvement in Physical Function After Coronary Artery Bypass Graft Surgery Using a Novel Rehabilitation Intervention
Bibliographic record
Abstract
PURPOSE: Cardiorespiratory and skeletal muscle deconditioning occurs following coronary artery bypass graft surgery and hospitalization. Outpatient, phase 2 cardiac rehabilitation (CR) is designed to remediate this deconditioning but typically does not begin until several weeks following hospital discharge. Although an exercise program between discharge and the start of CR could improve functional recovery, implementation of exercise at this time is complicated by postoperative physical limitations and restrictions. Our objective was to assess the utility of neuromuscular electrical stimulation (NMES) as an adjunct to current rehabilitative care following postsurgical discharge and prior to entry into CR on indices of physical function in patients undergoing coronary artery bypass graft surgery. METHODS: Patients were randomized to 4 wk of bilateral, NMES (5 d/wk) to their quadriceps muscles or no intervention (control). Physical function testing was performed at hospital discharge and 4 wk post-discharge using the Short Physical Performance Battery and the 6-min walk tests. Data from 37 patients (19 control/18 NMES) who completed the trial were analyzed. The trial was registered at ClinicalTrials.gov (NCT03892460). RESULTS: Physical function measures improved from discharge to 4 wk post-surgery across our entire cohort (P < .001). Patients randomized to NMES, however, showed greater improvements in 6-min walk test distance and power output compared with controls (P < .01). CONCLUSION: Our results provide evidence supporting the utility of NMES to accelerate recovery of physical function after coronary artery bypass graft surgery.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".