Sport-related concussion physician’s chart review – 2011–2016
Bibliographic record
Abstract
Objective To determine what proportion of patients experience an exacerbation of their symptoms as a result of premature return to play (RTP) and return to learn (RTL) following a sport-related concussion (SRC). Design Retrospective longitudinal chart review. Setting A sport medicine physician’s office in Ontario, Canada. Participants 266 cases related to 251 students with an SRC. Interventions A review of 266 electronic medical records (charts) of patients seen for SRC over a five-year period (2011–2016). Two blinded authors independently reviewed each chart and SCAT2 or SCAT3/Child SCAT3 symptom self report form. In situations where there was discrepancy between the two reviewers’ results, a third author reviewed the charts. Outcome measures remature RTP and RTL were defined as chart records documenting the recurrence or worsening of symptoms that accompanied the patients’ RTP or RTL. Main Results 403 cases were identified as concussion patients assessed. 266 were included as these cases were related to 251 students involved in a sport activity. Premature return to sport and to school were observed in 67 (25.19%) and 107 (40.23%) of the cases, respectively. Conclusions In our comparable study ending 5 years prior, premature return to sport and to school were observed in 43.5% and 44.7% of the cases, respectively. Despite changing our medical advice, based upon evolving expert recommendations on return to learn (RTL) after an SRC, premature RTL is still quite common. Efforts are needed to find the best method of implementing a coordinated plan for the post-concussion athlete who is returning to school. Competing interests None.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".