Heart rate variability and electrocardiogram waveform as predictors of morbidity during hypothermia and rewarming in rats
Bibliographic record
Abstract
This study examined electrocardiogram (ECG) waveform, heart rate (HR), mean blood pressure (BP), and HR variability as potential autonomic signatures of hypothermia and rewarming. Adult male Sprague-Dawley rats had telemetry transmitters surgically implanted, and 2 weeks were allowed for recovery prior to induction of hypothermia. Rats were lightly anesthetized (sodium pentobarbital, 35 mg/kg i.p.) and placed in a coil of copper tubing through which temperature-controlled water was circulated. Animals were cooled to a core temperature (Tc) of 20 degrees C, maintained there for 30 min, and then rewarmed. Data (Tc, BP, HR from ECG, and 10-s strips of ECG waveforms) were collected every 5 min throughout hypothermia and rewarming. Both HR and BP declined after initial increases with the drop in HR starting at a higher Tc than the drop in BP (29.6 +/- 2.4 degrees C vs. 27.1 +/- 3.3 degrees C, p < 0.05). Animals that were not successfully rewarmed exhibited a significant (p < 0.05) increase in the normalized standard deviation of interbeat intervals (IBI) throughout cooling compared with animals that were successfully rewarmed. The T wave of the ECG increased in amplitude and area with decreasing Tc. T-wave amplitude and IBI variability show potential as predictors of survival in hypothermic victims.
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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 | 0.000 |
| 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) | 0.000 | 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".