Aeromedical Transport in Children
Bibliographic record
Abstract
OBJECTIVE: Pediatric aeromedical transport (AT) is highly challenging. We aim to describe a series of 96 cases of children requiring medical transport in terms of the indication, modalities, and related adverse events. METHODS: In this single-center retrospective study, we included air-transported patients less than 18 years old. RESULTS: During the study period, 96 patients, with median age of 120 months (range, 0-204), were air transported. The reason for AT was repatriation to the home country from another hospital in 65 (67.7%), whereas for 31 (32.3%) patients, it was for transport from a hospital to another for a special procedure. The main diagnosis was trauma surgery (n = 38; 39.5%). Fifteen (15.6%) patients were mechanically ventilated. No patient sustained serious adverse events during the flight. Patients were transported by an air ambulance or by a scheduled aircraft in 55.2% and 44.8%, respectively. The median flight distance was 822 km (range, 277-9878), and most of the ATs were intra-European (n = 41; 42.7%). CONCLUSION: This study describes an international experience in providing AT services for pediatric clinical cases. Among pediatric patients, the younger ones constitute a specific population, and most of them require mechanical ventilation. Therefore, the transport of these patients seems to be more appropriate in a dedicated air ambulance.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".