The Myth of “Tongue Swallowing” Delays Cardiopulmonary Resuscitation of Athletes With Cardiac Arrest, Yet It Is Often Perpetuated by the Media
Bibliographic record
Abstract
BACKGROUND: tIn June 2021, during a Union of European Football Associations soccer competition, a Danish soccer player had cardiac arrest. Millions of spectators witnessed the event. The initial response of team players, attempting to prevent "tongue swallowing," was visible on television and was inaccurately portrayed as a "life-saving measure." METHODS: From 1990 to 2024, we continuously searched the Internet for videos showing athletes undergoing resuscitation maneuvers after collapsing during competition, focusing on the first response. We also analyzed the news coverage of these resuscitation efforts. RESULTS: We report 45 cases of athletes collapsing during sporting events that were caught on video or published and publicly available. When the first action was visible, an inappropriate response, including attempts to prevent tongue swallowing, preceded proper cardiopulmonary resuscitation (CPR) in 32 (84%) cases. Death or severe anoxic brain damage was more likely to follow cardiac arrest events when the victims were subjected to tongue-swallowing prevention maneuvers than when victims received CPR at first response (18 of 27 [67%] vs 0 of 3, P = 0.045). Twenty-eight cases were covered in a total of 84 news articles. The term "tongue swallowing" appeared in 40 articles and was generally praised, indicating that nearly half of the articles reinforced this misconception. CONCLUSIONS: During bystander resuscitation of athletes with cardiac arrest, attempts to prevent "tongue swallowing are common and are associated with a poor prognosis. Still, such attempts are praised by the media. Education on proper CPR techniques should include a critical reassessment of the myth of tongue swallowing.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".