Timing of Intracranial Pressure Monitoring in Traumatic Brain Injury: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVE: This study reviews the effect of the timing of intracranial pressure (ICP) monitor placement on mortality and length of hospital and intensive care unit stay outcomes. METHODS: This systematic review and meta-analysis adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines, searching 3 databases for English-language studies on traumatic brain injury (TBI) and ICP monitoring up to November 2024. The PECO framework defined eligibility criteria, focusing on patients with TBI, timing of ICP placement, and various outcomes. Two authors independently reviewed studies and extracted data, assessing bias using the Newcastle-Ottawa Scale. Statistical analyses were performed using R statistical software, applying random effects models for outcome comparisons. RESULTS: = 70%). Subgroup analyses based on age, disease severity, and time cutoff also yielded nonsignificant results. Publication bias assessments indicated no significant bias (P = 0.31). Additionally, no significant differences were found in hospital length of stay or intensive care unit length of stay. CONCLUSIONS: The systematic review and meta-analysis revealed no significant differences in mortality, hospital length of stay, and intensive care unit length of stay between early and late ICP monitoring in TBI patients. The lack of definitive evidence underscores the need for further research to establish optimal timing and improve clinical outcomes in TBI management.
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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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".