What are the most appropriate return-to-play guidelines for concussed child athletes?: Figure 1
Bibliographic record
Abstract
OBJECTIVE: To examine concussion literature for specific guidelines regarding return to play (RTP) following sport-related concussion in child athletes. To make recommendations regarding the most appropriate RTP guidelines for child athletes following sport-related concussion. DESIGN: A literature review of concussion literature. INTERVENTION: A literature search was conducted using Medline and Embase databases from 1998 to 2008. More than 60 articles and two websites were reviewed. RESULTS: There is a paucity of research on sport-related concussion in child athletes, particularly younger children (age 5-12 years). In particular, there is no research on RTP guidelines for child athletes following sport-related concussion. Child athletes take longer to recover from concussions than adults. Concussion symptoms may resolve before cognitive function has completely recovered. Concussion assessment and management in children can be confounded by their growth and development, as well as the lack of trained medical personnel involved with youth sports. There are no child-specific assessment tools for concussion. CONCLUSIONS: RTP decisions in children should be made cautiously and should be individualised. No concussed child athlete should be allowed to RTP the same day. Physical and cognitive rest is very important to allow for the resolution of concussion symptoms. Child athletes should remain symptom free for several days before starting a medically supervised stepwise exertion protocol. Further research is needed to elucidate the effects of concussion in children and to determine the most appropriate RTP guidelines. Child-specific concussion assessment tools need to be developed to improve concussion assessment and management in children.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.006 |
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".