Relationship between Measures of Cerebrovascular Reactivity and Intracranial Lesion Progression in Acute Traumatic Brain Injury Patients: A CENTER-TBI Study
Bibliographic record
Abstract
Failure of cerebral autoregulation has been linked to unfavorable outcome after traumatic brain injury (TBI). Preliminary evidence from a small, retrospective, single-center analysis suggests that autoregulatory dysfunction may be associated with traumatic lesion expansion, particularly for pericontusional edema. The goal of this study was to further explore these associations using prospective, multi-center data from the Collaborative European Neurotrauma Effectiveness Research in TBI (CENTER-TBI) and to further explore the relationship between autoregulatory failure, lesion progression, and patient outcome. A total of 88 subjects from the CENTER-TBI High Resolution ICU Sub-Study cohort were included. All patients had an admission computed tomography (CT) scan and early repeat scan available, as well as high-frequency neurophysiological recordings covering the between-scan interval. Using a novel, semiautomated approach at lesion segmentation, we calculated absolute changes in volume of contusion core, pericontusional edema, and extra-axial hemorrhage between the imaging studies. We then evaluated associations between cerebrovascular reactivity metrics and radiological lesion progression using mixed-model regression. Analyses were adjusted for baseline covariates and non-neurophysiological factors associated with lesion growth using multi-variate methods. Impairment in cerebrovascular reactivity was significantly associated with progression of pericontusional edema and, to a lesser degree, intraparenchymal hemorrhage. In contrast, there were no significant associations with extra-axial hemorrhage. The strongest relationships were observed between RAC-based metrics and edema formation. Pulse amplitude index showed weaker, but consistent, associations with contusion growth. Cerebrovascular reactivity metrics remained strongly associated with lesion progression after taking into account contributions from non-neurophysiological factors and mean cerebral perfusion pressure. Total hemorrhagic core and edema volumes on repeat CT were significantly larger in patients who were deceased at 6 months, and the amount of edema was greater in patients with an unfavourable outcome (Glasgow Outcome Scale-Extended 1-4). Our study suggests associations between autoregulatory failure, traumatic edema progression, and poor outcome. This is in keeping with findings from a single-center retrospective analysis, providing multi-center prospective data to support those results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".