Multiple trauma management in mountain environments - a scoping review
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: Multiple trauma in mountain environments may be associated with increased morbidity and mortality compared to urban environments. OBJECTIVE: To provide evidence based guidance to assist rescuers in multiple trauma management in mountain environments. ELIGIBILITY CRITERIA: All articles published on or before September 30th 2019, in all languages, were included. Articles were searched with predefined search terms. SOURCES OF EVIDENCE: PubMed, Cochrane Database of Systematic Reviews and hand searching of relevant studies from the reference list of included articles. CHARTING METHODS: Evidence was searched according to clinically relevant topics and PICO questions. RESULTS: Two-hundred forty-seven articles met the inclusion criteria. Recommendations were developed and graded according to the evidence-grading system of the American College of Chest Physicians. The manuscript was initially written and discussed by the coauthors. Then it was presented to ICAR MedCom in draft and again in final form for discussion and internal peer review. Finally, in a face-to-face discussion within ICAR MedCom consensus was reached on October 11th 2019, at the ICAR fall meeting in Zakopane, Poland. CONCLUSIONS: Multiple trauma management in mountain environments can be demanding. Safety of the rescuers and the victim has priority. A crABCDE approach, with haemorrhage control first, is central, followed by basic first aid, splinting, immobilisation, analgesia, and insulation. Time for on-site medical treatment must be balanced against the need for rapid transfer to a trauma centre and should be as short as possible. Reduced on-scene times may be achieved with helicopter rescue. Advanced diagnostics (e.g. ultrasound) may be used and treatment continued during transport.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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