Near-Infrared Spectroscopy Regional Oxygen Saturation Based Cerebrovascular Reactivity Assessments in Chronic Traumatic Neural Injury versus in Health: A Prospective Cohort Study
Bibliographic record
Abstract
)-based cerebrovascular reactivity (CVR) monitoring has enabled entirely non-invasive, continuous monitoring during both acute and long-term phases of care. To date, long-term post-injury CVR has not been properly characterized after acute traumatic neural injury, also known as traumatic brain injury (TBI). This study aims to compare CVR in those recovering from moderate-to-severe TBI with a healthy control group. A total of 101 heathy subjects were recruited for this study, along with 29 TBI patients. In the healthy cohort, the arterial blood pressure variant of the cerebral oxygen index (COx_a) was not statistically different between males and females or in the dominant and non-dominant hemispheres. In the TBI cohort, COx_a was not statistically different between the first and last available follow-up or by the side of cranial surgery. Surprisingly, CVR, as measured by COx_a, was statistically better in those recovering from TBI than those in the healthy cohort. In this prospective cohort study, CVR, as measured by NIRS-based methods, was found to be more active in those recovering from TBI than in the healthy cohort. This study may indicate that in individuals that survive TBI, CVR may be enhanced as a neuroprotective measure.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".