Abstract 41: Liquid Convection Surface Cooling Leads to High Rate of Recovery of Post-VT/VF Patients
Bibliographic record
Abstract
Introduction: Therapeutic hypothermia is an accepted standard of care for patients resuscitated from VT (ventricular tachycardia) and/or VF (ventricular fibrillation). Some prior studies have suggested that a faster time to target temperature may improve the chances of favorable neurological recovery. Hypothesis: We hypothesized that rapid cooling of post VT/VF patients using liquid convection surface cooling would lead to a high rate of recovery of such patients, compared to historical results with slower cooling methods. Methods: The Life Recovery Systems ThermoSuit System® was used to induce therapeutic hypothermia (approximately 33°C, maintained for 12 to 24 hours) in 37 post-resuscitation patients in 4 hospitals. Patient temperatures were monitored with an esophageal probe. Results were retrospectively analyzed for cooling rates, cardiac rhythm of VT/VF, favorable neurologic recovery (CPC 1 or 2), and adverse events. Results: Of the 37 patients, the mean cooling rate was 3.4 °C/hr (range 1.3-8.8). Of the 37 patients, 20 were resuscitated from VT or VF. Of these, 17 (85%) survived with favorable outcomes following the ThermoSuit treatment. There were no adverse events. Conclusions: Rapid induction of therapeutic hypothermia with the ThermoSuit System was associated with a very high rate of favorable neurologic recovery and an absence of adverse events in post-VT/VF patients. When compared with results of similar studies of slower cooling methods, these results suggest an advantage of faster cooling methods for the treatment of post-VT/VF patients.
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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) | 0.000 | 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) | 0.002 | 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".