• Zhihong Li, Feifei Xu, Taihui Zhang, Baocheng Zhao, Yaning Cai, Haigui Yang, Dongbo Li, Mingsheng Chen, Tianzhi Zhao, Xingye Zhang, Lanfu Zhao, Shunnan Ge, and Yan Qu.
• Department of Neurosurgery, Tangdu Hospital, Air Force Medical University, Xi'an, China.
• World Neurosurg. 2024 Jul 10.

ObjectivePatients with moderate traumatic brain injury (mTBI) are under the threat of intracranial hypertension (IHT). However, it is unclear which mTBI patient will develop IHT and should receive intracranial pressure (ICP)-lowering treatment or invasive ICP monitoring after admission. The purpose of the present study was to develop and validate a prediction model that estimates the risk of IHT in mTBI patients.MethodsBaseline data collected on admission of 296 mTBI patients with Glasgow Coma Scale (GCS) score of 9-11 was collected and analyzed. Multivariable logistic regression modeling with backward stepwise elimination was used to develop a prediction model for IHT. The discrimination efficacy, calibration efficacy, and clinical utility of the prediction model were evaluated. Finally, the prediction model was validated in a separate cohort of 122 patients from 3 hospitals.ResultsFour independent prognostic factors for IHT were identified: GCS score, Marshall head computed tomography score, injury severity score, and location of contusion. The C-statistic of the prediction model in internal validation was 84.30% (95% CI: 0.794-0.892). The area under the curve for the prediction model in external validation was 82.80% (95% CI: 0.747-0.909).ConclusionsA prediction model based on baseline parameters was found to be highly sensitive in distinguishing mTBI patients with GCS score of 9-11 who would suffer IHT. The high discriminative ability of the prediction model supports its use in identifying mTBI patients with GCS score of 9-11 who need ICP-lowering therapy or invasive ICP monitoring.Copyright © 2024. Published by Elsevier Inc.

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