Intracranial Pressure Monitoring and Treatment Thresholds in Acute Neural Injury: A Narrative Review of the Historical Achievements, Current State, and Future Perspectives
Bibliographic record
Abstract
Since its introduction in the 1960s, intracranial pressure (ICP) monitoring has become an indispensable tool in neurocritical care practice and a key component of the management of moderate/severe traumatic brain injury (TBI). The primary utility of ICP monitoring is to guide therapeutic interventions aimed at maintaining physiological ICP and preventing intracranial hypertension. The rationale for such ICP maintenance is to prevent secondary brain injury arising from brain herniation and inadequate cerebral blood flow. There exists a large body of evidence indicating that elevated ICP is associated with mortality and that aggressive ICP control protocols improve outcomes in severe TBI patients. Therefore, current management guidelines recommend a cerebral perfusion pressure (CPP) target range of 60-70 mm Hg and an ICP threshold of >20 or >22 mm Hg, beyond which therapeutic intervention should be initiated. Though our ability to achieve these thresholds has drastically improved over the past decades, there has been little to no change in the mortality and morbidity associated with moderate-severe TBI. This is a result of the "one treatment fits all" dogma of current guideline-based care that fails to take individual phenotype into account. The way forward in moderate-severe TBI care is through the development of continuously derived individualized ICP thresholds. This narrative review covers the topic of ICP monitoring in TBI care, including historical context/achievements, current monitoring technologies and indications, treatment methods, associations with patient outcome and multi-modal cerebral physiology, present controversies surrounding treatment thresholds, and future perspectives on personalized approaches to ICP-directed therapy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".