Injury in Brazilian Jiu-Jitsu Training
Bibliographic record
Abstract
BACKGROUND: Brazilian jiu-jitsu (BJJ) is a grappling-based martial art that can lead to injuries both in training and in competition. There is a paucity of data regarding injuries sustained while training in BJJ, in both competitive and noncompetitive jiu-jitsu athletes. HYPOTHESIS: We hypothesize that most BJJ practitioners sustain injuries to various body locations while in training and in competition. Our primary objective was to describe injuries sustained while training for BJJ, both in practice and in competition. Our secondary objectives were to classify injury type and to explore participant and injury characteristics associated with wanting to quit jiu-jitsu after injury. STUDY DESIGN: Descriptive epidemiology study. METHODS: We conducted a survey of all BJJ participants at a single club in Hamilton, Ontario, Canada. We developed a questionnaire including questions on demographics, injuries in competition and/or training, treatment received, and whether the participant considered discontinuing BJJ after injury. RESULTS: < 0.001). Two-thirds of injured participants required medical attention, with 15% requiring surgery. Participants requiring surgical treatment were 6.5 times more likely to consider quitting compared with those requiring other treatments, including no treatment (odds ratio [OR], 6.50; 95% CI, 1.53-27.60). Participants required to take more than 4 months off training were 5.5 times more likely to consider quitting compared with those who took less time off (OR, 5.48; 95% CI, 2.25-13.38). CONCLUSION: The prevalence of injury is very high among BJJ practitioners, with 9 of 10 practitioners sustaining at least 1 injury, commonly during training. Injuries were primarily sprains and strains to fingers, the upper extremity, and neck. Potential participants in BJJ should be informed regarding significant risk of injury and instructed regarding appropriate precautions and safety protocols. CLINICAL RELEVANCE: Clinicians should be aware of the substantial risk of injury among BJJ practitioners and the epidemiology of the injuries as outlined in this article.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".