EFFECT OF EXERCISE TRAINING ON HEALTH PERCEPTIONS IN ORGAN TRANSPLANT PATIENTS
Bibliographic record
Abstract
Organ transplant is an accepted treatment for end-stage organ disease. A return to a functional and physically active lifestyle with good quality of life is the desired procedural outcome of organ transplantation. PURPOSE: To examine the effects of 10 wks of upper body exercise training on health perceptions in organ transplant recipients (heart, lung, kidney, liver) and healthy controls. METHODS: Transplant patients (T, n = 19) and healthy sedentary controls (C, n = 7) were assessed with a Short-Form 36-Item health survey before and following 10 wks of Dragonboat training (2 d/wk). RESULTS: There were no significant differences pre-training between T and C in the following health domains: physical functioning; role limitations due to physical health; role limitations due to emotional health; vitality; general mental health; social functioning; and pain perception. General health perceptions were significantly (p < 0.05) higher in C vs. T both pre-(87 ± 5(SD)% vs. 69 ± 12%, respectively) and post-training (85 ± 11% vs. 76 ± 12%, respectively). Following training there were significant improvements in role limitations due to emotional health for C (81 ± 26% vs. 91 ± 25%) and T (88 ± 25% vs. 100 ± 0%). There were also significant improvements following training in vitality for C (70 ± 12% vs. 76 ± 10%) and T (72 ± 18% vs. 75 ± 12%). No other category showed any significant change following training. CONCLUSIONS: Organ transplant recipients and healthy sedentary controls experienced significant improvements in select health domains following 10 wks of Dragonboat training. These findings suggest that, while exercise training may improve health perception in organ transplant recipients, overall health perceptions of transplant recipients remain lower than those of controls. Funded by British Columbia Lung Association, Fujiwara Canada Inc., Novartis, and Roche Pharmaceuticals.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".