Epidemiology of illnesses encountered during a marathon race – an EMS perspective
Bibliographic record
Abstract
A total of 10,000 runners in the age group of 18-80 years, participated in the full (42.2 km) marathon, half (21.1 km) marathon and the 5 K run. Both trained and untrained runners took part in the race. Southern Indian city of Hyderabad, on the 24 of August from 5:00 AM to 1: 00 PM. Urban and semi-urban parts of the city with both paved and un-paved roads, maximum recorded temperature during the race was 35° Celsius. A prospective descriptive epidemiological analysis of race data of runners presenting with emergencies was done using a standardized patient data collection form given to medical aid providers. Triaging was done according to Canadian triage and acuity scale. Of 10,000 runners, 252 runners required medical assistance during the course of the race. Of all the patients presenting to EMS 248 were Triage priority 3 or 4 requiring urgent or less urgent care Exercise related musculoskeletal injuries accounted for 200 (79%) of the total cases Exercise related musculoskeletal injuries accounted for 200 (79%) of the total cases Dehydration related cramps accounted for 33 (13%) of the cases requiring oral or IV fluid rehydration Dehydration related cramps accounted for 33 (13%) of the cases requiring oral or IV fluid rehydration Terrain related blisters and foot injuries – 9 (3.5%) patients Terrain related blisters and foot injuries – 9 (3.5%) patients Vomitings - 4 (1.5%) Vomitings - 4 (1.5%) A total of 4 patients were triage priority 2 requiring Emergent care – Transported by EMS to the nearest tertiary care hospital. A 24 year old with symptomatic hypoglycaemia, requiring Dextrose infusion A 45 year old male with Altered mental status secondary to Heat exhaustion and hypotension requiring IV fluid resuscitation A 70 year old male with Hypotension and dizziness requiring IV fluid resuscitation A 23 year old girl who collapsed with hypotension and heat exhaustion requiring IV fluid resuscitation. Long-distance running can be a safe and benign sport; however there were serious heat related illnesses requiring hospitalization of runners in this study. A well prepared EMS system is paramount to hosting a marathon in India due to extreme temperatures and mass participation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".