Hyperspectral near infrared spectroscopy assessment of the brain during hypoperfusion
Bibliographic record
Abstract
Two-thirds of out-of-hospital cardiac arrest patients, who survive to hospital admission, die in the hospital from neurological injuries related to cerebral hypoperfusion. Hyperspectral near infrared spectroscopy (hNIRS) is a noninvasive technique that measures the major chromophores in the brain, such as oxygenated hemoglobin, deoxygenated hemoglobin and cytochrome C oxidase ([CCO]), an intracellular marker of oxygen consumption. We have demonstrated that hNIRS is feasible and can detect changes in cerebral oxygenation and metabolism in patients undergoing transcatheter aortic valve insertion (TAVI) – a procedure that temporarily induces sudden hypotension and hypoperfusion that mimics cardiac arrest. Using multi-distance hNIRS, we found that while measured regional oxygen saturation (rSO2) changes resulted mainly from the extra-cerebral tissues, [CCO] changes during cardiac arrests occurred mainly in the brains of patients. We also applied the hNIRS algorithm based on the “2-layer model” to the data to measure cerebral oxygen saturation and [CCO] in patients during the procedure.
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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) | 0.000 | 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".