Camping, Cowboys, and Country Music: Patient and Resource Management at Canada’s Largest Multi‐Day Country Music Festival
Bibliographic record
Abstract
mental status is one of the most common presentations to medical services at these events.It is challenging to care for these potentially critically ill patients, in and out of a hospital environment.To date, best management practices remain unclear for this common and high-risk subset of the festival population.Methods: We present a case series of patients presenting to medical services with an altered mental status, attending a 15,000 attendee, multi-day, electronic dance music event.A retrospective chart review was performed on patient encounter forms from 2014-2016 to identify alterations in patient content or consciousness.Results: Three event years were reviewed with 328 of 4,032 unique medical presentations deemed to have had altered content or consciousness.Of the altered content subset, 22 required physical or chemical restraint.Of the 255 altered consciousness presentations, 144 were transient syncope-like cases, 37 were seizure-like cases, and 41 had GCS <= 8 documented at some point during the visit.There were no endotracheal intubations or deaths.Seventy percent of altered patients stayed less than 30 minutes, and LOS was found to be inversely proportional to the lowest recorded GCS.Conclusion: Managing the altered patient at a music festival is challenging.True aspiration risk in the GCS <= 8 subset remains unclear.High risk features for poor outcomes in altered patients include significant desaturations, active vomiting in an unresponsive patient, metabolic abnormalities, associated trauma, severe agitation, and failure to meet discharge criteria.Analysis of medical presentations for altered mental status at a music festival suggest a handful of discrete clinical presentations and best practices.A good understanding of these presentations aids in preparing, training, and equipping for similar events.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".