120 Outcome Related Thresholds of Near Infrared Spectroscopy Based Cerebrovascular Reactivity Metrics in Moderate Severe TBI: A Canadian High Resolution-TBI (CAHR-TBI) Cohort Study
Bibliographic record
Abstract
INTRODUCTION: Dysfunctional cerebrovascular reactivity (CVR)/autoregulation contributes to secondary injury following traumatic brain injury (TBI). Currently, monitoring of CVR relies on intracranial pressure (ICP) monitoring and has known thresholds at which outcomes worsen. Interest has shifted to less invasive near infrared spectroscopic (NIRS) regional cerebral oxygen saturation (rSO2) based measures of CVR. However, threshold levels at which outcomes worsen have not yet been determined for these indices. METHODS: A retrospective multi-institutional cohort study utilizing the CAnadian High Resolution TBI (CAHR-TBI) Research Collaborative database was performed. The cohort included TBI patients with ICP, arterial blood pressure (ABP), and rSO2 monitoring treated in adult intensive care units (ICU). COx (using rSO2 and cerebral perfusion pressure) as well as COx_a (using rSO2 and ABP) were calculated for each subject as the rSO2 based indices of CVR. 2 x 2 tables were created grouping patients by alive/dead and favorable/unfavorable outcomes at various thresholds of COx and COx_a as well as rSO2 itself. Chi-square values were calculated and the threshold producing the highest value was identified as providing the best discriminative value. RESULTS: A total of 129 patients were included. For both COx and COx_a an optimal threshold value of 0.2 was identified for both survival (χ 2 = 9.57, p = 0.0020; χ 2 = 13.04, p = 0.0003 respectively) and favorable outcomes (χ 2 = 5.98, p = 0.0145; χ 2 = 8.94, p = 0.0028 respectively) with values above this associated with worse outcomes. Notably, there was no identifiable threshold for raw rSO2 values at which outcomes were identified to worsen. CONCLUSIONS: In this multi-institutional cohort study, COx and COx_a were found to have a uniform threshold of 0.2, above which clinical outcomes worsened. This study lays the groundwork to transition to less invasive means of continuously measuring CVR.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".