Articles: brain-injuries.
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Traumatic brain injury (TBI) is a major public health concern worldwide, contributing to high rates of injury-related death and disability. Severe traumatic brain injury (sTBI), although it accounts for only 10% of all TBI cases, results in a mortality rate of 30-40% and a significant burden of disability in those that survive. This study explored the potential of metabolomics in the diagnosis of sTBI and explored the potential of metabolomics to examine probable primary and secondary brain injury in sTBI. ⋯ The results demonstrate that serum metabolomics has diagnostic potential for sTBI and may reflect molecular mechanisms of primary and secondary brain injuries when comparing metabolite profiles between day 1 and day 4 post-injury. These early changes in serum metabolites may provide insight into molecular pathways or mechanisms of primary injury and ongoing secondary injuries, revealing potential therapeutic targets for sTBI. This work also highlights the need for further research and validation of sTBI metabolite biomarkers in a larger cohort.
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The oxygen reactivity index (ORx) reflects the correlation between focal brain tissue oxygen (pbtO2) and the cerebral perfusion pressure (CPP). Previous, small cohort studies were conflicting on whether ORx conveys cerebral autoregulatory information and if it is related to outcome in traumatic brain injury (TBI). Thus, we aimed to investigate these issues in a larger TBI cohort. ⋯ ORx seemed to be sensitive to the lower, but not the upper, limit of autoregulation, in contrast to PRx which was sensitive to both. The combination of high values for both ORx and PRx was particularly associated with worse outcome and, thus, ORx may provide a complementary value to the global index PRx. ORx could also be useful to determine the safe and dangerous perfusion target intervals.
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Patients supported by extracorporeal membrane oxygenation (ECMO) are at a high risk of brain injury, contributing to significant morbidity and mortality. This study aimed to employ machine learning (ML) techniques to predict brain injury in pediatric patients ECMO and identify key variables for future research. ⋯ The Random Forest model based on machine learning demonstrates high accuracy and robustness in predicting brain injury in pediatric patients supported by ECMO, with strong generalization capabilities and promising clinical applicability.
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Chinese medical journal · Jan 2025
ReviewBrain Injury Biomarkers and Applications in Neurological Diseases.
Neurological diseases are a major health concern, and brain injury is a typical pathological process in various neurological disorders. Different biomarkers in the blood or the cerebrospinal fluid are associated with specific physiological and pathological processes. ⋯ We aimed to summarize the applications of these biomarkers and their related interests and limits in the diagnosis and prognosis for neurological diseases, including traumatic brain injury, status epilepticus, stroke, Alzheimer's disease, and infection. In addition, a reasonable outlook for brain injury biomarkers as ideal detection tools for neurological diseases is presented.
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In this article, we explore the current literature on traumatic brain injury (TBI) in survivors of intimate partner violence (IPV) and evaluate the barriers to studying this vulnerable population. ⋯ Research on TBI and IPV is limited by multiple factors including mistrust of the healthcare system by survivors, lack of awareness by community advocates, and insufficient funding by public entities. As such, most investigations are small population, retrospective, and qualitative. Quantitative research addressing the scope of TBI in IPV found reported rates ranging from 19 to 100% of survivors experiencing neurological injury at the hands of a violent partner. The principals of trauma-informed healthcare should guide both neurological care for survivors as well as future studies on TBI and IPV, with an emphasis on community-based participatory research.