A paramedic-staffed medical rehydration unit at a mass gathering
Bibliographic record
Abstract
INTRODUCTION: Heat-related illness is reported to be a significant cause of morbidity at outdoor mass gatherings during warm weather. Paramedics are traditionally present at mass gatherings to provide prehospital care for people in need. OBJECTIVES: To describe a paramedic-staffed medical rehydration unit and a new role for paramedics at a mass gathering attended by more than 450,000 people. METHODS: A 48-bed medical rehydration unit was deployed adjacent to the main field hospital. Paramedics admitted patients to the unit if they met predetermined criteria for mild to moderate heat-related illness. Each paramedic was responsible for four beds. Paramedics initiated oral and intravenous rehydration therapy by following medical directives. Emergency medical services (EMS) physicians reviewed patients before discharge. RESULTS: The medical rehydration unit managed 143 patients (3/10,000 attendees). The mean number of patients admitted per hour was nine. The average age was 24 years; 103 (72%) were female. The main presenting complaint was syncope, presyncope, or dizziness in 43 (30%). Forty-four (31%) patients received parenteral and oral fluids; the remainder received oral fluids alone. The average length of stay was 94 minutes (95% CI 82-106). One hundred seven (75%) patients were discharged, 17 (12%) were transferred to the main field hospital, four (3%) left against medical advice, and two (1%) required transfer to a hospital off site. In 13 (9%) cases, records of patient disposition were incomplete. CONCLUSIONS: This article defines a new role for paramedics and describes the operation of a medical rehydration unit at a large, single-day mass gathering in summer.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".