Time spent above optimal cerebral perfusion pressure is not associated with failure to improve in outcome in traumatic brain injury
Bibliographic record
Abstract
BACKGROUND: Optimal cerebral perfusion pressure (CPPopt) has emerged as a promising personalized medicine approach to the management of moderate-to-severe traumatic brain injury (TBI). Though literature demonstrating its association with poor outcomes exists, there is yet to be work done on its association with outcome transition due to a lack of serial outcome data analysis. In this study we investigate the association between various metrics of CPPopt and failure to improve in outcome over time. METHODS: CPPopt was derived using three different cerebrovascular reactivity indices; the pressure reactivity index (PRx), the pulse amplitude index (PAx), and the RAC index. For each index, % times spent with cerebral perfusion pressure (CPP) above and below its CPPopt and upper and lower limits of reactivity were calculated. Patients were dichotomized based on improvement in Glasgow Outcome Scale-Extended (GOSE) scores into Improved vs. Not Improved between 1 and 3 months, 3 and 6 months, and 1- and 6-month post-TBI. Logistic regression analyses were then conducted, adjusting for the International Mission for Prognosis and Analysis of Clinical Trials (IMPACT) variables. RESULTS: This study included a total of 103 patients from the Winnipeg Acute TBI Database. Through Mann-Whitney U testing and logistic regression analysis, it was found that % time spent with CPP below CPPopt was associated with failure to improve in outcome, while % time spent with CPP above CPPopt was generally associated with improvement in outcome. CONCLUSIONS: Our study supports the existing narrative that time spent with CPP below CPPopt results in poorer outcomes. However, it also suggests that time spent above CPPopt may not be associated with worse outcomes and is possibly even associated with improvement in outcome.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 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".