Accidental cold-related injury leading to hospitalization in northern Sweden: an eight-year retrospective analysis
Bibliographic record
Abstract
BACKGROUND: Cold injuries are rare but important causes of hospitalization. We aimed to identify the magnitude of cold injury hospitalization, and assess causes, associated factors and treatment routines in a subarctic region. METHODS: In this retrospective analysis of hospital records from the 4 northernmost counties in Sweden, cases from 2000-2007 were identified from the hospital registry by diagnosis codes for accidental hypothermia, frostbite, and cold-water drowning. Results were analyzed for pre-hospital site events, clinical events in-hospital, and complications observed with mild (temperature 34.9 - 32°C), moderate (31.9 - 28°C) and severe (<28°C), hypothermia as well as for frostbite and cold-water drowning. RESULTS: From the 362 cases, average annual incidences for hypothermia, frostbite, and cold-water drowning were estimated to be 3.4/100,000, 1.5/100,000, and 0.8/100,000 inhabitants, respectively. Annual frequencies for hypothermia hospitalizations increased by approximately 3 cases/year during the study period. Twenty percent of the hypothermia cases were mild, 40% moderate, and 24% severe. For 12%, the lowest documented core temperature was 35°C or higher, for 4% there was no temperature documented. Body core temperature was seldom measured in pre-hospital locations. Of 362 cold injury admissions, 17 (5%) died in hospital related to their injuries. Associated co-factors and co-morbidities included ethanol consumption, dementia, and psychiatric diagnosis. CONCLUSIONS: The incidence of accidental hypothermia seems to be increasing in this studied sub-arctic region. Likely associated factors are recognized (ethanol intake, dementia, and psychiatric diagnosis).
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".