ABSTRACT
Acute ischemic stroke is a sudden neurological event caused by brain ischemia. Patients with large vessel occlusion are at high risk of developing significant cerebral edema, which can lead to rapid neurological decline. The optimal timing for decompressive hemicraniectomy to prevent further brain damage is still uncertain. This study aimed to identify potential predictors of severe brain edema. The data indicate that specific cytokines may help identify patients with a higher risk of developing life-threatening brain swelling in the early phase post-stroke. The association between a positive biomarker and the outcome was calculated, and three biomarkers-S100B protein, MMP-9, and IL-10-were found to be significantly associated with malignant edema. A model was derived for early predicting malignant cerebral edema, including S100B protein and IL-1 beta. These findings suggest that molecular biomarkers related to the ischemic cascade may be a helpful way of predicting the development of malignant cerebral edema in ischemic stroke patients, potentially widening the time window for intervention and assisting in decision-making. In conclusion, this study provides insights into the molecular mechanisms of severe brain edema and highlights the potential use of biomarkers in predicting the course of ischemic stroke.
Subject(s)
Brain Edema , Brain Ischemia , Ischemic Stroke , Stroke , Humans , Brain Edema/etiology , Ischemic Stroke/diagnosis , Ischemic Stroke/complications , Stroke/complications , Brain Ischemia/complications , Biomarkers , Case-Control Studies , S100 Calcium Binding Protein beta SubunitABSTRACT
Abstract Multidrug-resistant tuberculosis (MDRTB) is a serious world health problem that limits public actions to control tuberculosis, because the most used anti-tuberculosis first-line drugs fail to stop mycobacterium spread. Consequently, a quick detection through molecular diagnosis is essential to reduce morbidity and medical costs. Despite the availability of several molecular-based commercial-kits to diagnose multidrug-resistant tuberculosis, their diagnostic value might diverge worldwide since Mycobacterium tuberculosis genetic variability differs according to geographic location. Here, we studied the predictive value of four common mycobacterial mutations in strains isolated from endemic areas of Brazil. Mutations were found at the frequency of 41.9% for katG, 25.6% for inhA, and 69.8% for rpoB genes in multidrug-resistant strains. Multimarker analysis revealed that combination of only two mutations (“katG/S315T + rpoB/S531L”) was a better surrogate of multidrug-resistant tuberculosis than single-marker analysis (86% sensitivity vs. 62.8%). Prediction of multidrug-resistant tuberculosis was not improved by adding a third or fourth mutation in the model. Therefore, rather than using diagnostic kits detecting several mutations, we propose a simple dual-marker panel to detect multidrug-resistant tuberculosis, with 86% sensitivity and 100% specificity. In conclusion, this approach (previous genetic study + analysis of only prevalent markers) would considerably decrease the processing costs while retaining diagnostic accuracy.
Subject(s)
Humans , Bacterial Proteins/genetics , DNA-Directed RNA Polymerases/genetics , Catalase/genetics , Drug Resistance, Multiple, Bacterial/genetics , Isoniazid/pharmacology , Antitubercular Agents/pharmacology , Rifampin/pharmacology , DNA, Bacterial , Microbial Sensitivity Tests , Genetic Markers , Polymerase Chain Reaction , Predictive Value of Tests , Sensitivity and Specificity , Tuberculosis, Multidrug-Resistant/microbiology , Genotype , Mutation/genetics , Mycobacterium tuberculosis/drug effects , Mycobacterium tuberculosis/geneticsABSTRACT
Multidrug-resistant tuberculosis (MDRTB) is a serious world health problem that limits public actions to control tuberculosis, because the most used anti-tuberculosis first-line drugs fail to stop mycobacterium spread. Consequently, a quick detection through molecular diagnosis is essential to reduce morbidity and medical costs. Despite the availability of several molecular-based commercial-kits to diagnose multidrug-resistant tuberculosis, their diagnostic value might diverge worldwide since Mycobacterium tuberculosis genetic variability differs according to geographic location. Here, we studied the predictive value of four common mycobacterial mutations in strains isolated from endemic areas of Brazil. Mutations were found at the frequency of 41.9% for katG, 25.6% for inhA, and 69.8% for rpoB genes in multidrug-resistant strains. Multimarker analysis revealed that combination of only two mutations ("katG/S315T+rpoB/S531L") was a better surrogate of multidrug-resistant tuberculosis than single-marker analysis (86% sensitivity vs. 62.8%). Prediction of multidrug-resistant tuberculosis was not improved by adding a third or fourth mutation in the model. Therefore, rather than using diagnostic kits detecting several mutations, we propose a simple dual-marker panel to detect multidrug-resistant tuberculosis, with 86% sensitivity and 100% specificity. In conclusion, this approach (previous genetic study+analysis of only prevalent markers) would considerably decrease the processing costs while retaining diagnostic accuracy.
