Articles: traumatic-brain-injuries.
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Curr Opin Anaesthesiol · Oct 2022
ReviewCerebral metabolic derangements following traumatic brain injury.
Outcome following traumatic brain injury (TBI) remains variable, and derangements in cerebral metabolism are a common finding in patients with poor outcome. This review compares our understanding of cerebral metabolism in health with derangements seen following TBI. ⋯ Mitochondrial dysfunction and the use of alternative energy substrates are potential therapeutic targets, but improved understanding of the causes, impact and significance of metabolic derangements in clinical TBI are needed. Maintaining adequate oxygen and glucose delivery across the injured brain may accelerate the recovery of mitochondrial function and cerebral energy metabolism and remain important management targets.
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Journal of neurotrauma · Oct 2022
Diffusion Tensor Imaging Reveals Elevated Diffusivity of White Matter Microstructure that is Independently Associated with Long-Term Outcome after Mild Traumatic Brain Injury: A TRACK-TBI Study.
Diffusion tensor imaging (DTI) literature on single-center studies contains conflicting results regarding acute effects of mild traumatic brain injury (mTBI) on white matter (WM) microstructure and the prognostic significance. This larger-scale multi-center DTI study aimed to determine how acute mTBI affects WM microstructure over time and how early WM changes affect long-term outcome. From Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI), a cohort study at 11 United States level 1 trauma centers, a total of 391 patients with acute mTBI ages 17 to 60 years were included and studied at two weeks and six months post-injury. ⋯ At two weeks post-injury, global WM AD and MD were both independently associated with six-month incomplete recovery (GOSE <8 vs = 8) even after accounting for demographic, clinical, and other imaging factors. DTI provides reliable imaging biomarkers of dynamic WM microstructural changes after mTBI that have utility for patient selection and treatment response in clinical trials. Continued technological advances in the sensitivity, specificity, and precision of diffusion magnetic resonance imaging hold promise for routine clinical application in mTBI.
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Journal of neurotrauma · Oct 2022
ReviewRemote follow-up technologies in traumatic brain injury: a scoping review.
Traumatic brain injury (TBI) remains a leading cause of death and disability worldwide. Motivations for outcome data collection in TBI are threefold: to improve patient outcomes, to facilitate research, and to provide the means and methods for wider injury surveillance. Such data play a pivotal role in population health, and ways to increase the reliability of data collection following TBI should be pursued. ⋯ Where reported, clinical facilitators, remote follow-up timing and intervals between sessions, synchronicity of follow-up instances, proxy involvement, outcome measures utilized, and technology evaluation efforts are described. FUTs can aid more temporally sensitive assessments and capture fluctuating sequelae, a benefit of particular relevance to TBI cohorts. However, the evidence base surrounding FUTs remains in its infancy, particularly with respect to large samples, low- and middle-income patient cohorts, and the validation of outcome measures for deployment via such remote technology.
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Journal of neurotrauma · Oct 2022
Association between Blood and CT Imaging Biomarkers in a Cohort of Mild Traumatic Brain Injury Patients.
The objective of this work was to analyze the relationships between traumatic brain injury (TBI) on computed tomographic (CT) imaging and blood concentration of glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCH-L1), and S100B. This prospective cohort study involved 644 TBI patients referred to Stanford Hospital's Emergency Department between November 2015 and April 2017. Plasma and serum samples of 462 patients were analyzed for levels of GFAP, UCH-L1, and S100B. ⋯ In conclusion, GFAP, UCH-L1, and S100B show high sensitivity and negative predictive values for all types of TBI lesions on head CT. A combination of negative blood biomarkers (GFAP and UCH-L1) in a patient suspected of TBI may be used to safely obviate the need for a head CT scan. GFAP is a promising indicator to discriminate between small and large/diffuse TBI lesions.
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Randomized Controlled Trial
Machine Learning-Based Prognostic Model for the Prediction of Early Death after Traumatic Brain Injury: Comparison with the Corticosteroid Randomization after Significant Head Injury (CRASH) Model.
Machine learning (ML) has been used to predict the outcomes of traumatic brain injury. However, few studies have reported the use of ML models to predict early death. This study aimed to develop ML models for early death prediction and to compare performance with the corticosteroid randomization after significant head injury (CRASH) model. ⋯ The ML models may have comparable performances compared to the CRASH model despite being developed with a smaller sample size.