Optimal Control of Inspired Perfluorocarbon Temperature for Ultrafast Hypothermia Induction by Total Liquid Ventilation in an Adult Patient Model
Bibliographic record
Abstract
GOAL: Recent preclinical studies have shown that therapeutic hypothermia induced in less than 30 min by total liquid ventilation (TLV) strongly improves the survival rate after cardiac arrest. When the lung is ventilated with a breathable perfluorocarbon liquid, the inspired perfluorocarbon allows us to control efficiently the cooling process of the organs. While TLV can rapidly cool animals, the cooling speed in humans remains unknown. The objective is to predict the efficiency and safety of ultrafast cooling by TLV in adult humans. METHODS: It is based on a previously published thermal model of ovines in TLV and the design of a direct optimal controller to compute the inspired perfluorocarbon temperature profile. The experimental results in an adult sheep are presented. The thermal model of sheep is subsequently projected to a human model to simulate the optimal hypothermia induction and its sensitivity to physiological parameter uncertainties. RESULTS: The results in the sheep showed that the computed inspired perfluorocarbon temperature command can avoid arterial temperature undershoot. The projection to humans revealed that mild hypothermia should be ultrafast (reached in fewer than 3 min (-72 °C/h) for the brain and 20 min (-10 °C/h) for the entire body). CONCLUSION: The projection to human model allows concluding that therapeutic hypothermia induction by TLV can be ultrafast and safe. SIGNIFICANCE: This study is the first to simulate ultrafast cooling by TLV in a human model and is a strong motivation to translate TLV to humans to improve the quality of life of postcardiac arrest patients.
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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 | 0.000 | 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 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".