The Assessment of Airway Maneuvers and Interventions in University Canadian Football, Ice Hockey, and Soccer Players
Bibliographic record
Abstract
CONTEXT: Managing an airway in an unconscious athlete is a lifesaving skill that may be made more difficult by the recent changes in protective equipment. Different airway maneuvers and techniques may be required to help ventilate an unconscious athlete who is wearing full protective equipment. OBJECTIVE: To assess the effectiveness of different airway maneuvers with football, ice hockey, and soccer players wearing full protective equipment. DESIGN: Crossover study. SETTING: University sports medicine clinic. PATIENTS OR OTHER PARTICIPANTS: A total of 146 university varsity athletes, consisting of 62 football, 45 ice hockey, and 39 soccer players. INTERVENTION(S): Athletes were assessed for different airway and physical characteristics. Three investigators then evaluated the effectiveness of different bag-valve-mask (BVM) ventilation techniques in supine athletes who were wearing protective equipment while inline cervical spine immobilization was maintained. MAIN OUTCOME MEASURE(S): The effectiveness of 1-person BVM ventilation (1-BVM), 2-person BVM ventilation (2-BVM), and inline immobilization and ventilation (IIV) was judged by each investigator for each athlete using a 4-point rating scale. RESULTS: All forms of ventilation were least difficult in soccer players and most difficult in football players. When compared with 1-BVM, both 2-BVM and IIV were deemed more effective by all investigators for all athletes. Interference from the helmet and stabilizer were common reasons for difficult ventilation in football and ice hockey players. CONCLUSIONS: Sports medicine professionals should practice and be comfortable with different ventilation techniques for athletes wearing full equipment. The use of a new ventilation technique, termed inline immobilization and ventilation, may be beneficial, especially when the number of responders is limited.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".