Twenty-Five Years of Intracranial Pressure Monitoring After Severe Traumatic Brain Injury: A Retrospective, Single-Center Analysis
Bibliographic record
Abstract
BACKGROUND: Intracranial pressure (ICP) is a clinically important variable after severe traumatic brain injury (TBI) and has been monitored, along with clinical outcome, for over 25 yr in Addenbrooke's hospital, Cambridge, United Kingdom. This time period has also seen changes in management strategies with the implementation of protocolled specialist neurocritical care, expansion of neuromonitoring techniques, and adjustments of clinical treatment targets. OBJECTIVE: To describe the changes in intracranial monitoring variables over the past 25 yr. METHODS: Data from 1146 TBI patients requiring ICP monitoring were analyzed. Monitored variables included ICP, cerebral perfusion pressure (CPP), and the cerebral pressure reactivity index (PRx). Data were stratified into 5-yr epochs spanning the 25 yr from 1992 to 2017. RESULTS: CPP increased sharply with specialist neurocritical care management (P < 0.0001) (introduction of a specific TBI management algorithm) before stabilizing from 2000 onwards. ICP decreased significantly over the 25 yr of monitoring from an average of 19 to 12 mmHg (P < 0.0001) but PRx remained unchanged. The mean number of ICP plateau waves and the number of patients developing refractory intracranial hypertension both decreased significantly. Mortality did not significantly change in the cohort (22%). CONCLUSION: We demonstrate the evolving trends in neurophysiological monitoring over the past 25 yr from a single, academic neurocritical care unit. ICP and CPP were responsive to the introduction of an ICP/CPP protocol while PRx has remained unchanged.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".