Rapid Weight Loss of Up to Five Percent of the Body Mass in Less Than 7 Days Does Not Affect Physical Performance in Official Olympic Combat Athletes With Weight Classes: A Systematic Review With Meta-Analysis
Bibliographic record
Abstract
Given the relevance of the effects that weight loss can generate on the physical performance in athletes, this study performed a systematic review with meta-analysis of the published literature on rapid weight loss (RWL) and examined its impact on the physical performance in Official Olympic combat sports athletes. The “Preferred Reporting Items for Systematic Reviews and Meta-Analysis” (PRISMA) guidelines were followed to ensure an ethical and complete reporting of the findings. PubMed, SPORT Discus, and EBSCO were the electronic databases explored for article retrieval and selection. The following string was applied: “RWL” OR “weight loss” OR “weight reduction” AND “judo” OR “wrestling” or “taekwondo” or “boxing” AND “performance.” Based on the quality analysis, conducted according to the “Tool for the assessment of study quality and reporting in exercise training studies” (TESTEX), ten articles achieved a score >6 points. The meta-analysis showed a significant difference in pre- vs. post-weight loss (p = 0.003) and no effects in pre- vs. post-power and strength performance analysis (p > 0.05 for both results). Based on our systematic review and meta-analysis of the literature, RWL up to ≤5% of the body mass in less than 7 days does not influence performance outcomes in Official Olympic combat athletes with weight classes, considering the strength and power measures.
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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 | 0.019 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.053 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".