Racing in Rising Global Temperatures: A Scoping Review of Heat-related Illnesses in Endurance Running
Bibliographic record
Abstract
OBJECTIVES: As temperatures globally continue to rise, sporting events such as marathons will take place on warmer days, increasing the risk of exertional heat stroke (EHS). METHODS: The medical librarian developed and executed comprehensive searches in Ovid MEDLINE, Ovid Embase, CINAHL, SPORTDiscus, Scopus, and Web of Science Core Collection. Relevant keywords were selected. The results underwent title, abstract, and full text screening in a web-based tool called Covidence, and were analyzed for pertinent data. RESULTS: A total of 3918 results were retrieved. After duplicate removal and title, abstract, and full text screening, 38 articles remained for inclusion. There were 22 case reports, 12 retrospective reviews, and 4 prospective observational studies. The races included half marathons, marathons, and other long distances. In the case reports and retrospective reviews, the mean environmental temperatures were 21.3°C and 19.8°C, respectively. Discussions emphasized that increasing environmental temperatures result in higher incidences of EHS. CONCLUSION: With rising global temperatures from climate change, athletes are at higher risk of EHS. Early ice water immersion is the best treatment for EHS. Earlier start times and cooling stations for races may mitigate incidences of EHS. Future work needs to concentrate on the establishment of EHS prevention and mitigation protocols.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".