Field Torso-Warming Modalities: A Comparative Study Using a Human Model
Bibliographic record
Abstract
OBJECTIVE: To compare four field-appropriate torso-warming modalities that do not require alternating-current (AC) electrical power, using a human model of nonshivering hypothermia. METHODS: Five subjects, serving as their own controls, were cooled four times in 8 degrees C water for 10-30 minutes. Shivering was inhibited by buspirone (30 mg) taken orally prior to cooling and intravenous (IV) meperidine (1.25 mg/kg) at the end of immersion. Subjects were hoisted out of the water, dried, and insulated and then underwent 120 minutes of one of the following: spontaneous warming only; a charcoal heater on the chest; two flexible hot-water bags (total 4 liters of water at 55 degrees C, replenished every 20 minutes) applied to the chest and upper back; or two chemical heating pads applied to the chest and upper back. Supplemental meperidine (maximum cumulative dose of 3.5 mg/kg) was administered as required to inhibit shivering. RESULTS: The postcooling afterdrop (i.e., the continued decrease in body core temperature during the early period of warming), compared with spontaneous warming (2.2 degrees C), was less for the chemical heating pads (1.5 degrees C) and the hot-water bags (1.6 degrees C, p < 0.05) and was 1.8 degrees C for the charcoal heater. Subsequent core rewarming rates for the hot-water bags (0.7 degree C/h) and the charcoal heater (0.6 degree C/h) tended to be higher than that for the chemical heating pads (0.2 degree C/h) and were significantly higher than that for spontaneous warming rate (0.1 degrees C/h, p < 0.05). CONCLUSION: In subjects with shivering suppressed, greater sources of external heat were effective in attenuating core temperature afterdrop, whereas sustained sources of external heat effectively established core rewarming. Depending on the scenario and available resources, we recommend the use of charcoal heaters, chemical heating pads, or hot-water bags as effective means for treating cold patients in the field or during transport to definitive care.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".