Prehospital Resuscitation of the Buried Avalanche Victim
Bibliographic record
Abstract
In North America and Europe, approximately 150 people die of avalanches per year, and fatalities are presumed to be many times higher in developing countries. Four factors are decisive for survival: grade of burial, duration of burial, presence of an air pocket and a free airway, and severity of trauma. According to Swiss data, the overall mortality rate with avalanche burial is 23%, but it largely depends on the grade of burial. While the mortality rate is 52.4% in completely buried (head below the snow) victims in the Swiss population, it is only 4.2% in partially buried (head free) victims. Additionally, survival in completely buried victims drops to 30% within the first 35 min, initially due to death from lethal trauma, followed by asphyxia in 20-35 min. Thereafter, survival decreases more gradually and victims who are not fatally injured and are able to breath under the snow slowly succumb to hypoxia, hypercapnia, and hypothermia. In the absence of fatal injuries, rescue strategies depend on the duration of burial and the victim's core temperature. With a burial time<35 min, survival depends on preventing asphyxia by rapid extrication, adequate airway management, and cardiopulmonary resuscitation. With a burial time>35 min, tackling hypothermia is of utmost importance. Therefore, gentle extrication and continuous core temperature and electrocardiogram monitoring are recommended. Pulseless victims with a patent airway and a core temperature<32°C should receive uninterrupted cardiopulmonary resuscitation and be transported to a hospital with extracorporeal rewarming facilities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".