A prospective study of concussions among National Hockey League players during regular season games: the NHL-NHLPA Concussion Program
Bibliographic record
Abstract
BACKGROUND: In 1997, the National Hockey League (NHL) and NHL Players' Association (NHLPA) launched a concussion program to improve the understanding of this injury. We explored initial postconcussion signs, symptoms, physical examination findings and time loss (i.e., time between the injury and medical clearance by the physician to return to competitive play), experienced by male professional ice-hockey players, and assessed the utility of initial postconcussion clinical manifestations in predicting time loss among hockey players. METHODS: We conducted a prospective case series of concussions over seven NHL regular seasons (1997-2004) using an inclusive cohort of players. The primary outcome was concussion and the secondary outcome was time loss. NHL team physicians documented post-concussion clinical manifestations and recorded the date when a player was medically cleared to return to play. RESULTS: Team physicians reported 559 concussions during regular season games. The estimated incidence was 1.8 concussions per 1000 player-hours. The most common postconcussion symptom was headache (71%). On average, time loss (in days) increased 2.25 times (95% confidence interval [CI] 1.41-3.62) for every subsequent (i.e., recurrent) concussion sustained during the study period. Controlling for age and position, significant predictors of time loss were postconcussion headache (p < 0.001), low energy or fatigue (p = 0.01), amnesia (p = 0.02) and abnormal neurologic examination (p = 0.01). Using a previously suggested time loss cut-point of 10 days, headache (odds ratio [OR] 2.17, 95% CI 1.33-3.54) and low energy or fatigue (OR 1.72, 95% CI 1.04-2.85) were significant predictors of time loss of more than 10 days. INTERPRETATION: Postconcussion headache, low energy or fatigue, amnesia and abnormal neurologic examination were significant predictors of time loss among professional hockey players.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".