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Intracranial Pressure as a Dynamic Predictor of Traumatic Brain Injury Outcomes: A Scoping Review.
John H Kanter1,2, Robert C Osorio3, Abel Torres-Espin4,5
1Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.
Journal of Neurotrauma
|September 29, 2025
Summary
Serial intracranial pressure (ICP) monitoring in severe traumatic brain injury (TBI) predicts outcomes. Combining ICP data with cerebrovascular reactivity and using machine learning shows promise for personalized TBI management.
Area of Science:
- Neurosurgery
- Critical Care Medicine
- Neurology
Background:
- Intracranial pressure (ICP) monitoring is vital for severe traumatic brain injury (TBI) management.
- Its role as a dynamic outcome predictor is continually evolving.
- Advanced modeling, including machine learning, is emerging for ICP analysis.
Purpose of the Study:
- To evaluate serial ICP measurements as a predictor of TBI outcomes.
- To integrate ICP data with cerebrovascular reactivity metrics.
- To identify trends in ICP modeling, particularly machine learning approaches.
Main Methods:
- A scoping review following PRISMA-ScR guidelines was conducted.
- Systematic database searches covered publications from January 1998 to August 2024.
- Data from 29 studies (N=5,743 patients) were synthesized.
Main Results:
- Specific ICP patterns significantly correlate with clinical outcomes, including mortality.
- Early ICP monitoring (within 72 hours) and threshold-dependent predictions are valuable.
- Integrating ICP with cerebrovascular reactivity enhances predictive accuracy.
Conclusions:
- Dynamic ICP patterns strongly associate with mortality and functional outcomes in TBI.
- ICP is increasingly viewed as a multidimensional metric.
- Machine learning and advanced techniques offer potential for precision TBI medicine, but standardization is needed.
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