Journal of neurotrauma
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Journal of neurotrauma · Jun 2024
Review Comparative StudyComparing Randomized Controlled Trials of Moderate to Severe Traumatic Brain Injury in Lower to Middle Income Countries versus High Income Countries.
Outcomes from traumatic brain injury (TBI) including death differ significantly between high-, middle-, and low-income countries. Little is known, however, about differences in TBI research across the globe. The objective of this article was to examine randomized controlled trials (RCTs) of moderate-to-severe TBI in high-income countries (HICs) compared with low- and middle-income countries (LMICs), as defined by the World Bank income per capita cutoff of $13,205 US dollars. ⋯ The 62.6% of RCTs from LMICs were conducted in the acute phase post-injury (≤1 month) compared with 42.1% of RCTs from HICs. Of RCTs from LMICs, 92.4% focused on medical/surgical management compared with 52.5% from HICs. Since 2016, more RCTs have been conducted in LMICs than in HICs, indicating the importance of better understanding this pattern of research output.
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Journal of neurotrauma · Jun 2024
Lack of association of informant-reported traumatic brain injury and chronic traumatic encephalopathy.
Repetitive head impacts (RHIs) from football are associated with the neurodegenerative tauopathy chronic traumatic encephalopathy (CTE). It is unclear whether a history of traumatic brain injury (TBI) is sufficient to precipitate CTE neuropathology. We examined the association between TBI and CTE neuropathology in 580 deceased individuals exposed to RHIs from football. ⋯ There was no association between CTE neuropathology status or severity and TBI with LOC (odds ratio [OR] = 0.95, 95% confidence interval [CI] = 0.64-1.41; OR = 1.22, 95% CI = 0.71-2.09) or msTBI (OR = 0.70, 95% CI = 0.33-1.50; OR = 1.01, 95% CI = 0.30-3.41). There were no associations with other neurodegenerative or cerebrovascular pathologies examined. TBI with LOC and msTBI were not associated with CTE neuropathology in this sample of brain donors exposed to RHIs from American football.
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Journal of neurotrauma · Jun 2024
Multicenter StudyDiagnostic Utility of Glial Fibrillary Acidic Protein Beyond 12 Hours After Traumatic Brain Injury: A TRACK-TBI Study.
Blood levels of glial fibrillary acidic protein (GFAP) and ubiquitin carboxyl-terminal hydrolase-L1 (UCH-L1) within 12h of suspected traumatic brain injury (TBI) have been approved by the Food and Drug administration to aid in determining the need for a brain computed tomography (CT) scan. The current study aimed to determine whether this context of use can be expanded beyond 12h post-TBI in patients presenting with Glasgow Coma Scale (GCS) 13-15. The prospective, 18-center Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study enrolled TBI participants aged ≥17 years who presented to a United States Level 1 trauma center and received a clinically indicated brain CT scan within 24h post-injury, a blood draw within 24h and at 14 days for biomarker analysis. ⋯ The GFAP provided good discrimination in the overall cohort at days 1 (AUC = 0.82) and 14 (AUC = 0.72), and in the hospitalized subgroup at days 1 (AUC = 0.84), 3 (AUC = 0.88), 5 (AUC = 0.82), and 14 (AUC = 0.74). The UCH-L1, NSE, and S100B did not perform well (AUC = 0.51-0.57 across time points). This study demonstrates the utility of GFAP to aid in decision-making for diagnostic brain CT imaging beyond the 12h time frame in patients with TBI who have a GCS 13-15.
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Journal of neurotrauma · Jun 2024
Observational StudyAssociation Between Early External Ventricular Drain Insertion And Functional Outcomes Six-months Following Moderate-to-Severe Traumatic Brain Injury.
Traumatic brain injury (TBI) is a leading global cause of morbidity and mortality. Intracranial hypertension following moderate-to-severe TBI (m-sTBI) is a potentially modifiable secondary cerebral insult and one of the central therapeutic targets of contemporary neurocritical care. External ventricular drain (EVD) insertion is a common therapeutic intervention used to control intracranial hypertension and attenuate secondary brain injury. ⋯ Following adjustment for the IMPACT (International Mission for Prognosis and Analysis of Clinical Trials in TBI) score extended (Core + CT), sex, injury severity score, study and treatment site, patients receiving a late EVD had higher odds of death or severe disability (GOSE 1-4) at 6 months follow-up than those receiving an early EVD adjusted odds ratio; 95% confidence interval, 2.14; 1.22-3.76; p = 0.008. Our study suggests that in patients with m-sTBI where an EVD is needed, early (≤ 24 h post-injury) insertion may result in better long-term functional outcomes. This finding supports future prospective investigation in this area.
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Journal of neurotrauma · Jun 2024
Development of a Multimodal Machine Learning-Based Prognostication Model for Traumatic Brain Injury Using Clinical Data and Computed Tomography Scans: A CENTER-TBI and CINTER-TBI Study.
Computed tomography (CT) is an important imaging modality for guiding prognostication in patients with traumatic brain injury (TBI). However, because of the specialized expertise necessary, timely and dependable TBI prognostication based on CT imaging remains challenging. This study aimed to enhance the efficiency and reliability of TBI prognostication by employing machine learning (ML) techniques on CT images. ⋯ The developed model achieved superior performance without the necessity for manual CT assessments (AUC = 0.846 [95% CI: 0.843-0.849]) compared with the model based on the clinical and laboratory variables (AUC = 0.817 [95% CI: 0.814-0.820]) and established CT scoring systems requiring manual interpretations (AUC = 0.829 [95% CI: 0.826-0.832] for Marshall and 0.838 [95% CI: 0.835-0.841] for International Mission for Prognosis and Analysis of Clinical Trials in TBI [IMPACT]). The external validation demonstrated the prognostic capacity of the developed model to be significantly better (AUC = 0.859 [95% CI: 0.857-0.862]) than the model using clinical variables (AUC = 0.809 [95% CI: 0.798-0.820]). This study established an ML-based model that provides efficient and reliable TBI prognosis based on CT scans, with potential implications for earlier intervention and improved patient outcomes.