Anabolic Effect of Exercise Training in People with End-Stage Renal Disease on Hemodialysis: A Systematic Review with Meta-analysis
Bibliographic record
Abstract
PURPOSE: The primary purpose of this systematic review was to evaluate the anabolic effect of exercise intervention in adults with end-stage renal disease on hemodialysis (HD). The secondary objectives were to evaluate the influences of participant characteristics and exercise parameters on changes in muscle size. METHODS: Electronic databases (Cochrane, CINAHL, EMBASE, PEDro, PubMed and SCOPUS) were searched from inception to November 2012. Randomized clinical trials published in English that included adults on HD undergoing an exercise intervention where muscle mass was measured as an outcome were included in this review. Two reviewers independently selected the studies, extracted data, and assessed risk of bias within the included studies. RESULTS were then combined by meta-analysis. The effect of exercises was determined using a standardized mean difference (SMD), expressed as Hedges' g, computed using a random effects model. RESULTS: Seven SMDs extracted from five studies were included for final analysis. Strength training was used in all studies; one study used aerobic and mixed strength and aerobic training with two subgroups of participants. The overall effect of exercise on muscle mass was statistically significant (SMD: 0.272; 95% CI, 0.020-0.525). CONCLUSIONS: Our results confirm a small but significant effect of strengthening exercise as an anabolic intervention to increase muscle mass. Exercise training should be included in routine management of people on maintenance HD. Although current results indicate that one in nine people on HD is likely to benefit from exercise intervention, parameters influencing these results require further research.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".