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High-Frequency Physiological Measures Predict Post-Admission Surgical Intervention After Severe Traumatic Brain
Sarah Hinds1,2, Claudia Robertson3, Jingxiao Chen1
1Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
Journal of Neurotrauma
|November 22, 2025
Summary
Predicting the need for neurosurgery after traumatic brain injury is crucial. Machine learning models using intracranial pressure and blood pressure data can forecast cranial surgery requirements hours in advance, aiding timely interventions.
Area of Science:
- Neurosurgery
- Critical Care Medicine
- Biomedical Engineering
Background:
- Traumatic brain injury (TBI) frequently leads to intracranial complications requiring surgical intervention.
- Approximately 12% of TBI patients need surgery for issues like intracranial hemorrhage or elevated intracranial pressure (ICP).
Purpose of the Study:
- To identify factors associated with surgical intervention in TBI patients.
- To evaluate the predictive capability of longitudinal physiological measurements for cranial surgery needs.
Main Methods:
- Analysis of high-frequency physiological data (including ICP) from 288 patients across four studies.
- Utilized machine learning and statistical models, including random forests, to predict surgery occurrence.
- Compared model performance using the area under the receiving operating characteristic curve (AUC).
Main Results:
- Key predictors for cranial surgery included ICP and mean arterial pressure (MAP) dynamics (means, medians, transgressions) and ICP slope over 6 hours pre-surgery.
- The random forests model achieved the highest predictive performance with an AUC of 0.75.
- Physiological data trends significantly correlated with the need for craniectomy or craniotomy.
Conclusions:
- Longitudinal physiological monitoring, particularly ICP and MAP, can predict the need for emergent neurosurgery in TBI patients.
- Machine learning models offer a promising tool for early surgical risk stratification.
- Early prediction may facilitate timely intervention, potentially mitigating secondary brain injury from elevated ICP.
