Deaths in triathletes: immersion pulmonary oedema as a possible cause
Bibliographic record
Abstract
BACKGROUND/AIM: To address the question as to whether immersion pulmonary oedema (IPO) may be a common cause of death in triathlons, markers of swimming-induced pulmonary oedema (SIPO) susceptibility were sought in triathletes' postmortem examinations. METHODS: Deaths while training for or during triathlon events in the USA and Canada from October 2008 to November 2015 were identified, and postmortem reports requested. We assessed obvious causes of death; the prevalence of left ventricular hypertrophy (LVH); comparison with healthy triathletes. RESULTS: We identified 58 deaths during the time period of the review, 42 (72.4%) of which occurred during a swim. Of these, 23 postmortem reports were obtained. Five individuals had significant (≥70%) coronary artery narrowing; one each had coronary stents; retroperitoneal haemorrhage; or aortic dissection. 9 of 20 (45%) with reported heart mass exceeded 95th centile values. LV free wall and septal thickness were reported in 14 and 9 cases, respectively; of these, 6 (42.9%) and 4 (44.4%) cases exceeded normal values. 6 of 15 individuals (40%) without an obvious cause of death had excessive heart mass. The proportion of individuals with LVH exceeded the prevalence in the general triathlete population. CONCLUSIONS: LVH-a marker of SIPO susceptibility-was present in a greater than the expected proportion of triathletes who died during the swim portion. We propose that IPO may be a significant aetiology of death during the swimming phase in triathletes. The importance of testing for LVH in triathletes as a predictor of adverse outcomes should be explored further.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".