Combining H-FABP and GFAP increases the capacity to differentiate between CT-positive and CT-negative patients with mild traumatic brain injury
| Autor: | Carmen Melinda Prica, Jean-Charles Sanchez, Alejandro Bustamante, Amir El Rahal, Lara Rinaldi, Roser García-Armengol, Linnéa Lagerstedt, Andereggen E, Juan José Egea-Guerrero, Joan Montaner, Karl Lothard Schaller, Asita Sarrafzadeh, Ana Rodríguez-Rodríguez, Manuel Quintana-Díaz |
|---|---|
| Přispěvatelé: | Instituto de Biomedicina de Sevilla (IBIS) |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Male
Serum Proteins Critical Care and Emergency Medicine Traumatic Brain Injury lcsh:Medicine Pathology and Laboratory Medicine Biochemistry Vascular Medicine Gastroenterology Diagnostic Radiology Cohort Studies 0302 clinical medicine Traumatic brain injury Medicine and Health Sciences Brain Damage 030212 general & internal medicine lcsh:Science Tomography Trauma Medicine ddc:616 Multidisciplinary Radiology and Imaging Brain Middle Aged Interleukin-10 Neurology Cohort Computed axial tomography Biomarker (medicine) Female medicine.symptom Traumatic Injury Fatty Acid Binding Protein 3 Research Article medicine.medical_specialty Imaging Techniques Serum proteins Neuroimaging Hemorrhage Brain damage S100 Calcium Binding Protein beta Subunit Research and Analysis Methods Sensitivity and Specificity Diagnosis Differential 03 medical and health sciences Signs and Symptoms Text mining Diagnostic Medicine Internal medicine Glial Fibrillary Acidic Protein medicine Humans Brain Concussion ddc:613 business.industry lcsh:R Glasgow Coma Scale Biology and Life Sciences Proteins medicine.disease Triage Diagnostic medicine Computed Axial Tomography Institutional repository Lesions lcsh:Q business Tomography X-Ray Computed Neurotrauma 030217 neurology & neurosurgery Biomarkers Neuroscience |
| Zdroj: | PLOS ONE, Vol. 13, No 7 (2018) P. e0200394 idUS. Depósito de Investigación de la Universidad de Sevilla instname Repositorio Institucional de la Consejería de Sanidad de la Comunidad de Madrid Consejería de Sanidad de la Comunidad de Madrid Dipòsit Digital de Documents de la UAB Universitat Autònoma de Barcelona PLoS ONE, Vol 13, Iss 7, p e0200394 (2018) Digital.CSIC. Repositorio Institucional del CSIC PLoS ONE |
| ISSN: | 1932-6203 |
| Popis: | Mild traumatic brain injury (mTBI) patients may have trauma-induced brain lesions detectable using CT scans. However, most patients will be CT-negative. There is thus a need for an additional tool to detect patients at risk. Single blood biomarkers, such as S100B and GFAP, have been widely studied in mTBI patients, but to date, none seems to perform well enough. In many different diseases, combining several biomarkers into panels has become increasingly interesting for diagnoses and to enhance classification performance. The present study evaluated 13 proteins individually—H-FABP, MMP-1, MMP-3, MMP-9, VCAM, ICAM, SAA, CRP, GSTP, NKDA, PRDX1, DJ-1 and IL-10—for their capacity to differentiate between patients with and without a brain lesion according to CT results. The best performing proteins were then compared and combined with the S100B and GFAP proteins into a CT-scan triage panel. Patients diagnosed with mTBI, with a Glasgow Coma Scale score of 15 and one additional clinical symptom were enrolled at three different European sites. A blood sample was collected at hospital admission, and a CT scan was performed. Patients were divided into two two-centre cohorts and further dichotomised into CT-positive and CT-negative groups for statistical analysis. Single markers and panels were evaluated using Cohort 1. Four proteins—H-FABP, IL-10, S100B and GFAP—showed significantly higher levels in CT-positive patients. The best-performing biomarker was H-FABP, with a specificity of 32% (95% CI 23–40) and sensitivity reaching 100%. The best-performing two-marker panel for Cohort 1, subsequently validated in Cohort 2, was a combination of H-FABP and GFAP, enhancing specificity to 46% (95% CI 36–55). When adding IL-10 to this panel, specificity reached 52% (95% CI 43–61) with 100% sensitivity. These results showed that proteins combined into panels could be used to efficiently classify CT-positive and CT-negative mTBI patients. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|