P.119 NIRS regional oxygen saturation based cerebrovascular reactivity in the recovery from moderate/severe TBI
Bibliographic record
Abstract
Background: Near-infrared spectroscopy (NIRS) regional cerebral oxygen saturation (rSO 2 ) based cerebrovascular reactivity (CVR) indicies have enable the entirely non-invasive continuous monitoring. This study aims to compare CVR in those recovering from moderate/severe TBI to a health control group. Methods: In this prospective cohort study the cerebral oxygen CVR index, COx_a (using rSO 2 and arterial blood pressure), was measured in subjects with moderate/severe TBI at follow-up. COx_a was also measured in a group of healthy controls. CVR was compared within and between these groups using conventional statistics. Results: A total of 101 heathy subject were recruited for this study along with 29 TBI patients. In the health cohort COx_a was not statistically different between males and females or in the dominate and non-dominate hemisphere. The TBI cohort, COx_a was not statistically different between first and last available follow up. Surprisingly, CVR as measured by COx_a was statistically better in those recovering from TBI than in the healthy cohort. Conclusions: In the prospective cohort study, CVR as measured by NIRS based methods, was found to be more active in those recovering from TBI than in a healthy cohort. This study may indicate that, in those 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 | 0.000 | 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) | 0.005 | 0.001 |
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".