Predictive Modeling of Neurosurgical Intervention and Mortality in Traumatic Brain Injury: Experience from a Level I Trauma Center Pubblico

Abstract

Introduction: Traumatic brain injury (TBI) affects thousands at Grady Memorial Hospital (GMH) annually. Prognostication and management are challenging and lack standardization, especially in grave cases. Given the impact of early decisions, including limitation of life-sustaining treatment, improving prognostication is essential to balance chances of favorable recovery with morbidity, mortality, and public health issues, including resource expenditure.

 

Methods: Analyses incorporated 6567 TBI patients presenting to GMH from 2016-2021, and 135 were excluded due to arrival without signs of life. Two multivariable logistic regression models were used to evaluate predictors of neurosurgical intervention among all TBI patients (model 1) and those with Glasgow Coma Scale (GCS) of 3-5 (model 2). The corresponding regression analyses assessing predictors of mortality were denoted as models 3 and 4. The models were assessed for collinearity and presented as adjusted odds ratios (OR) with 95% confidence intervals (CI). C-statistics were calculated to evaluate predictive strength of each model.

 

Results: Presence of major extracranial injury, as evidenced by Injury Severity Score (ISS) ³ 15 (OR= 13.5, CI 8.3, 23.6) was the only significant predictor in model 1 (C-statistic 0.768). In model 2, sex (male vs. female (OR=3.1, 2.1, 10.4)) and major extracranial injury (OR=19.1, 5.3, 125) were significant predictors (C-statistic 0.827). In model 3, significant prognosticating factors included age (55-64 (OR=1.9, 1.1, 3.2), 65-74 (OR=2.0, 1.1, 3.6), greater than 75 (OR=1.9, 1.0, 3.5), vs. 18-29 years), race (other vs. Black (OR=0.4, 0.1, 0.8)), hypoxia (OR=3.9, 2.2, 7.0), and major extracranial injury (OR=34.1, 16.5, 87.1) (C-statistic=0.812). In model 4, age (65-74 (OR=9.8, 1.5, 84.9), greater than 75 (OR=10.0, 1.4, 95.2) vs. 18-29 years), and mechanism of injury (road traffic collision (RTC) vs. fall (OR=3.53, 1.1, 12.9) were significant predictors (C-statistic=0.740).  

 

Conclusion: The strongest predictors of neurosurgical intervention were male sex, among patients with GCS 3-5, and major extracranial injury in both groups; however, GCS was not significantly associated. With respect to in-hospital mortality, age and presence of major extracranial injury were significantly predictive in both groups along with hypoxia among all TBI patients. Additionally, RTC mechanism of injury was a significant predictor of mortality in the GCS 3-5 group.

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School	Rollins School of Public Health
Department	Epidemiology
Subfield / Discipline	Global Epidemiology - MPH & MSPH
Degree	M.P.H.
Submission	Master's Thesis
Language	English
Research Field	Health Sciences, Medicine and Surgery
Parola chiave	Epidemiology Logistic Regression Traumatic Brain Injury Prognostication Ethics
Committee Chair / Thesis Advisor	Michael Goodman, Emory University

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