Acute clinical signs and outcome of concussion in National Hockey League (NHL) players
Bibliographic record
Abstract
Objectives To describe and quantify the acute clinical signs of concussion in National Hockey League (NHL) players. Setting National Hockey League (NHL). Design Prospective case series of concussions over a 5 year period of regular season NHL games (2006–2011). Subjects Digital video images of 341 NHL players diagnosed with concussions. Outcome Measures Primary outcome measures were mechanism of contact (direct vs indirect trauma), observable acute clinical signs (eg, disorientation, loss of consciousness, balance difficulties, ‘slow to get up’), and time loss that is, time between the injury and medical clearance by the physician to return to competitive play). Results Approximately 20% of players diagnosed with concussions showed no on-ice clinical signs. Most frequent on-ice clinical signs were: (1) slow to get up; (2) clutching of the head/helmet; and (3) disorientation/dazed. The number of players with observable on-ice clinical signs, particularly for those who either sustained ‘Possible/Probable Loss of Consciousness’ declined following the 2009 season. None of the clinical signs predicted poor outcome (eg, greater than 21 days of time loss). Conclusions Concussion can produce a spectrum of acute on-ice clinical signs. Most commonly observed with the 5 year sample of NHL players were ‘slow to get up’, ‘clutching of the head/helmet’, and ‘disorientation/dazed’. Length of time to recovery was not predicted on the basis of acute observable signs. Competing interests One of the authors (PC) is a paid consultant for the National Hockey League Players' Association (NHLPA).
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".