Time-to-Referral, Use, and Efficacy of Cardiac Rehabilitation After Heart Transplantation
Bibliographic record
Abstract
BACKGROUND: Timely access, adherence, and efficacy of cardiac rehabilitation programs (CRP) are important given the potential to mitigate or reverse the side effects of immunosuppressive medications, weight gain, and cardiovascular deconditioning that place heart transplant (HT) recipients at increased cardiovascular risk. However, there is a dearth of information on use and efficacy of CRPs. Therefore, we examined process indicators (time to referral and correlates, program adherence) and clinical outcome indicators (functional capacity (VO(2peak)), anthropometrics) of CR post-HT compared to post-coronary artery bypass graft (CABG). METHODS: Baseline, 6-month exercise stress test results, and anthropometrics were examined retrospectively among consecutively enrolled post-HT and age-matched and sex-matched CABG patients. Time to referral and program entry, attendance, and completion rates were also measured. RESULTS: Heart transplant (n=43) and CABG patients were referred 24.9 ± 48.9 and 2.1 ± 3.6 months, respectively, after surgery (P=0.003). Once referred, there was no difference in elapsed-time to program entry (P=0.2). There was a positive relationship between time to referral and baseline waist circumference (r=0.5, P=0.001), body mass index (r=0.5, P=0.002), hip circumference (r=0.4, P=0.008), and body fat percentage (r=0.4, P=0.03) in HT. Heart transplant and CABG patients had similar rates of CRP dropout (27.9% vs. 37.2% respectively, P=0.4). There was improvement in VO(2peak) for HT (2.4 ± 4.2 mL/kg/min; P=0.02) and CABG (5.5 ± 5.4 mL/kg/min, P<0.001), but was greater for CABG (P=0.04). Anthropometric measures remained stable for both cohorts (P>0.05). CONCLUSION: There is a lengthy delay in time from HT to CRP referral, though once referred, gain significant benefit in functional capacity. The appropriateness of this wait needs to be elucidated; however, it appears that longer wait times are associated with adverse effects on body composition.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".