Electroencephalogram biomarkers as predictors of mortality and functional recovery in patients with severe traumatic brain injury: Protocol study

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES MethodsX Pub Date : 2024-12-28 DOI:10.1016/j.mex.2024.103146
Walter Gomes da Silva Filho , Layza Julhia do Nascimento Moura , Arthur Barcelos Massariol Nascimento , Gabrielle Cristina Tessmann , Fabricia Silva Miranda , Vitória Caroline Reinoso de Almeida , Bárbara Vargens Broedel , Miller Lucas de Faria , Fernando Zanela da Silva Arêas
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Abstract

Traumatic brain injury (TBI) is a global public health condition that causes cognitive and behavioral deficits. This protocol assesses the potential of quantitative electroencephalogram (EEG) biomarkers, associated with inflammatory indicators, to predict mortality and functional recovery in patients with severe TBI. Through continuous monitoring and analysis of abnormal brain activity patterns, the protocol aims to personalize therapeutic interventions and improve patient quality of life. This randomized clinical trial includes 84 adult participants with severe TBI, followed at different stages of recovery, using validated scales for functional and predictive analysis. Traumatic brain injury (TBI) is a globally impactful public health condition characterized by initial brain injuries caused by traumatic forces, leading to cognitive and behavioral deficits. The trauma triggers inflammatory and neurochemical changes that exacerbate neuronal damage, resulting in neuropsychiatric complications. The use of electroencephalogram (EEG), particularly in its quantitative form (QEEG), is crucial for patients with severe TBI, as it allows early detection of abnormal brain activity patterns, such as slow waves, which indicate a worse prognosis. This continuous monitoring, combined with inflammatory biomarkers, guides personalized therapeutic interventions and improves the prediction of clinical outcomes, contributing to patient quality of life.

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MethodsX
MethodsX Health Professions-Medical Laboratory Technology
CiteScore
3.60
自引率
5.30%
发文量
314
审稿时长
7 weeks
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