Cerebral Perfusion Pressure in Severe Traumatic Brain Injury Survivors and Non-Survivors: A Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Severe traumatic brain injury (sTBI) is a leading cause of death and disability worldwide. Cerebral perfusion pressure (CPP), the difference between mean arterial and intracranial pressure, is crucial for maintaining cerebral blood flow. However, the optimal CPP threshold for improving outcomes remains uncertain. OBJECTIVE: To identify CPP levels associated with favorable outcomes following sTBI through a systematic review and meta-analysis. METHODS: Following PRISMA guidelines, we systematically searched PubMed, Scopus, and Web of Science up to February 2024 for studies involving adult sTBI patients admitted to intensive care units. Studies reporting CPP in relation to outcomes measured by the Glasgow Outcome Scale (GOS) were included. Pooled mean CPP differences between outcome groups were calculated using a random-effects model. Study quality was assessed using the Newcastle-Ottawa Scale, and evidence certainty was evaluated with GRADE. RESULTS: < 0.05). Survivors also demonstrated higher CPP than non-survivors (mean difference 8.15 mmHg; 95% CI: 3.28-13.02). Evidence quality ranged from low to very low due to study heterogeneity. CONCLUSIONS: Higher CPP levels (~75-80 mmHg) are associated with better survival and functional outcomes after sTBI, supporting individualized, multimodal CPP management rather than a fixed 60 mmHg threshold.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.036 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".