期刊
JOURNAL OF NEUROTRAUMA
卷 36, 期 20, 页码 2863-2871出版社
MARY ANN LIEBERT, INC
DOI: 10.1089/neu.2018.5809
关键词
biomarker; GFAP; S100B; traumatic brain injury; UCH-L1
资金
- National Institutes of Neurological Disorders and Stroke [1R01NS071867]
- National Institute of Neurological Disorders and Stroke of the National Institutes of Health [NS062778, 5U10NS059032, U01NS056975, R01 NS071867]
- National Center for Advancing Translational Sciences of the National Institutes of Health [UL1TR000454]
- Emory Emergency Neurosciences Laboratory in the Department of Emergency Medicine, Emory School of Medicine, and Grady Memorial Hospital
Rapid risk-stratification of patients with acute traumatic brain injury (TBI) would inform management decisions and prognostication. The objective of this serum biomarker study (Biomarkers of Injury and Outcome [BIO]-Progesterone for Traumatic Brain Injury, Experimental Clinical Treatment [ProTECT]) was to test the hypothesis that serum biomarkers of structural brain injury, measured at a single, very early time-point, add value beyond relevant clinical covariates when predicting unfavorable outcome 6 months after moderate-to-severe acute TBI. BIO-ProTECT utilized prospectively collected samples obtained from subjects with moderate-to-severe TBI enrolled in the ProTECT III clinical trial of progesterone. Serum samples were obtained within 4 h after injury. Glial fibrillary acidic protein (GFAP), S100B, alpha II-spectrin breakdown product of molecular weight 150 (SBDP150), and ubiquitin C-terminal hydrolase-L1 (UCH-L1) were measured. The association between log-transformed biomarker levels and poor outcome, defined by a Glasgow Outcome Scale-Extended (GOS-E) score of 1-4 at 6 months post-injury, were estimated via logistic regression. Prognostic models and a biomarker risk score were developed using bootstrapping techniques. Of 882 ProTECT III subjects, samples were available for 566. Each biomarker was associated with 6-month GOS-E (p < 0.001). Compared with a model containing baseline patient variables/characteristics, inclusion of S100B and GFAP significantly improved prognostic capacity (p <= 0.05 both comparisons); conversely, UCH-L1 and SBDP did not. A final predictive model incorporating baseline patient variables/characteristics and biomarker data (S100B and GFAP) had the best prognostic capability (area under the curve [AUC] = 0.85, 95% confidence interval [CI]: CI 0.81-0.89). Very early measurements of brain-specific biomarkers are independently associated with 6-month outcome after moderate-to-severe TBI and enhance outcome prediction.
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