Comparison of Heat Donation Through the Head or Torso on Mild Hypothermia Rewarming
Bibliographic record
Abstract
OBJECTIVE: The purpose of the study was to compare the effectiveness of head vs torso warming in rewarming mildly hypothermic, vigorously shivering subjects using a similar source of heat donation. METHODS: Six subjects (1 female) were cooled on 3 occasions in 8 ºC water for 60 minutes or to a core temperature of 35 ºC. They were then dried, insulated, and rewarmed by 1) shivering only; 2) charcoal heater applied to the head; or 3) charcoal heater applied to the torso. The order of rewarming methods followed a balanced design. Esophageal temperature, skin temperature, heart rate, oxygen consumption, and heat flux were measured. RESULTS: There were no significant differences in rewarming rate among the 3 conditions. Torso warming increased skin temperature and inhibited shivering heat production, thus providing similar net heat gain (268 ± 66 W) as did shivering only (355 ± 105 W). Head warming did not inhibit average shivering heat production (290 ± 72 W); it thus provided a greater net heat gain during 35 to 60 minutes of rewarming than did shivering only. CONCLUSIONS: Head warming is as effective as torso warming for rewarming mildly hypothermic victims. Head warming may be the preferred method of rewarming in the field management of hypothermic patients if: 1) extreme conditions in which removal of the insulation and exposure of the torso to the cold is contraindicated; 2) excessive movement is contraindicated (eg, potential spinal injury or severe hypothermia that has a risk of ventricular fibrillation); or 3) if emergency personnel are working on the torso.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".