Incidence and predictors of critical events during urgent air-medical transport
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Little is known about the risks of urgent air-medical transport used in regionalized health care systems. We sought to determine the incidence of in-transit critical events and identify factors associated with these events. METHODS: We conducted a population-based, retrospective cohort study using clinical and administrative data. We included all adults undergoing urgent air-medical transport in the Canadian province of Ontario between Jan. 1, 2004, and May 31, 2006. The primary outcome was in-transit critical events, which we defined as death, major resuscitative procedure, hemodynamic deterioration, or inadvertent extubation or respiratory arrest. RESULTS: We identified 19 228 patients who underwent air-medical transport during the study period. In-transit critical events were observed in 5.1% of all transports, for a rate of 1 event per 12.6 hours of transit time. Events consisted primarily of new hypotension or airway management procedures. Independent predictors of critical events included female sex (adjusted odds ratio [OR] 1.3, 95% confidence interval [CI] 1.1-1.5), assisted ventilation before transport (adjusted OR 3.0, 95% CI 2.3-3.7), hemodynamic instability before transport (adjusted OR 3.2, 95% CI 2.5-4.1), transport in a fixed-wing aircraft (adjusted OR 1.5, 95% CI 1.2-1.8), increased duration of transport (adjusted OR 1.02 per 10-minute increment, 95% CI 1.01-1.03), on-scene calls (adjusted OR 1.7, 95% CI 1.4-2.1) and type of crew (adjusted OR 0.6 for advanced care paramedics v. critical care paramedics, 95% CI 0.5-0.7). INTERPRETATION: Critical events occurred in about 1 in every 20 air-medical transports and were associated with multiple risk factors at the patient, transport and system levels. These findings have implications for the refinement of training of paramedic transport crews and processes for triage and transport.
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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 | 0.005 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it