Epidemiologic features of medical emergencies in remote First Nations in northern Ontario: a cross-sectional descriptive study using air ambulance transport data
Bibliographic record
Abstract
BACKGROUND: For about 25 000 Ontarians living in remote northern First Nations communities, seeing a doctor in an emergency department requires flying in an airplane or helicopter. This study describes the demographic and epidemiologic characteristics of patients transported from these communities to access hospital-based emergency medical care. METHODS: In this cross-sectional descriptive study, we examined primary medical data on patient transportation from Ornge, the provincial medical air ambulance service provider, for 26 remote Nishnawbe Aski Nation communities in northern Ontario from 2012 to 2016. We described these transports using univariate descriptive statistics. RESULTS: Over the 5-year study period, 10 538 patients (mean 2107.6 per year) were transported by Ornge from the 26 communities. Transport incidence ranged from 9.2 to 9.5 per 100 on-reserve population per year. Women aged 65 years or more had the highest transport incidence (25.9 per 100). Girls aged 5-9 years had the lowest mean incidence (2.1 per 100). Gastrointestinal issues accounted for 13.3% of transfers. Neurologic issues, respiratory issues and trauma each accounted for about 11% of transfers, and cardiac issues for 9.6%. Patients with obstetric issues accounted for 7.6% of transfers per year, and toxicologic emergencies for 7.5%. INTERPRETATION: This study provides the epidemiologic foundation to improve emergency care and emergency transport from remote First Nation communities in Ontario.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".