Cerebral Oxygen Saturation: Graded Response to Carbon Dioxide with Isoxia and Graded Response to Oxygen with Isocapnia
Bibliographic record
Abstract
BACKGROUND: Monitoring cerebral saturation is increasingly seen as an aid to management of patients in the operating room and in neurocritical care. How best to manipulate cerebral saturation is not fully known. We examined cerebral saturation with graded changes in carbon dioxide tension while isoxic and with graded changes in oxygen tension while isocapnic. METHODOLOGY/PRINCIPAL FINDINGS: The study was approved by the Research Ethics Board of the University Health Network at the University of Toronto. Thirteen studies were undertaken in healthy adults with cerebral oximetry by near infrared spectroscopy. End-tidal gas concentrations were manipulated using a model-based prospective end-tidal targeting device. End-tidal carbon dioxide was altered ±15 mmHg from baseline in 5 mmHg increments with isoxia (clamped at 110±4 mmHg). End-tidal oxygen was changed to 300, 400, 500, 80, 60 and 50 mmHg under isocapnia (37±2 mmHg). Twelve studies were completed. The end-tidal carbon dioxide versus cerebral saturation fit a linear relationship (R(2) = 0.92±0.06). The end-tidal oxygen versus cerebral saturation followed log-linear behaviour and best fit a hyperbolic relationship (R(2) = 0.85±0.10). Cerebral saturation was maximized in isoxia at end-tidal carbon dioxide of baseline +15 mmHg (77±3 percent). Cerebral saturation was minimal in isocapnia at an end-tidal oxygen tension of 50 mmHg (61±3 percent). The cerebral saturation during normoxic hypocapnia was equivalent to normocapnic hypoxia of 60 mmHg. CONCLUSIONS/SIGNIFICANCE: Hypocapnia reduces cerebral saturation to an extent equivalent to moderate hypoxia.
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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) | 0.001 | 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".