Medical repatriation via fixed‐wing air ambulance: a review of patient characteristics and adverse events
Bibliographic record
Abstract
Anaesthetists are often employed as medical escorts for patients undergoing international transfer by air ambulance. There is little published data on the types of patients being transferred and on the incidence of adverse events. We performed a retrospective review of the documentation of all air ambulance transfers performed by a single company over a 2-year period followed by a prospective assessment of all high-risk patients transferred over a 1-year period. Of 483 transfers identified, 47% were defined as high-risk and 20% were of patients receiving mechanical ventilation. In the prospective group, 28% of patients required pretransfer optimisation, 7% required a major therapeutic intervention during transfer and there was a major adverse event in 12% of transfers. There were two deaths during transport. These data support the recommendation that escorting personnel should be from an appropriate speciality, have reasonable seniority and be adequately trained and supervised.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".