Diffuse Intracranial Injury Patterns Are Associated with Impaired Cerebrovascular Reactivity in Adult Traumatic Brain Injury: A CENTER-TBI Validation Study
Bibliographic record
Abstract
Recent single-center retrospective analysis displayed the association between admission computed tomography (CT) markers of diffuse intracranial injury and worse cerebrovascular reactivity. The goal of this study was to further explore these associations using the prospective multi-center Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) high-resolution intensive care unit (HR ICU) data set. Using the CENTER-TBI HR ICU sub-study cohort, we evaluated those patients with both archived high-frequency digital physiology (100 Hz or higher) and the presence of a digital admission CT scan. Physiological signals were processed for pressure reactivity index (PRx) and both the percent (%) time above defined PRx thresholds and mean hourly dose above threshold. Admission CT injury scores were obtained from the database. Quantitative contusion, edema, intraventricular hemorrhage (IVH), and extra-axial lesion volumes were obtained via semi-automated segmentation. Comparison between admission CT characteristics and PRx metrics was conducted using Mann-U, Jonckheere-Terpstra testing, with a combination of univariate linear and logistic regression techniques. A total of 165 patients were included. Cisternal compression and high admission Rotterdam and Helsinki CT scores, and Marshall CT diffuse injury sub-scores were associated with increased percent (%) time and hourly dose above PRx threshold of 0, +0.25, and +0.35 (p < 0.02 for all). Logistic regression analysis displayed an association between deep peri-contusional edema and mean PRx above a threshold of +0.25. These results suggest that diffuse injury patterns, consistent with acceleration/deceleration forces, are associated with impaired cerebrovascular reactivity. Diffuse admission intracranial injury patterns appear to be consistently associated with impaired cerebrovascular reactivity, as measured through PRx. This is in keeping with the previous single-center retrospective literature on the topic. This study provides multi-center validation for those results, and provides preliminary data to support potential risk stratification for impaired cerebrovascular reactivity based on injury pattern.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".