The prognostic value of neuron-specific enolase in head trauma patients.
ABSTRACT In recent years, in addition to neurological examination and neuroradiologic examinations, attempts have been made to assess the severity of post-traumatic brain injury and to obtain an early idea of patient prognosis using biochemical markers with a high degree of brain tissue specificity. One such enzyme is neuron-specific enolase (NSE). This study investigates the correlation between serum NSE levels, Glasgow Coma Score, and prognosis measured by Glasgow Outcome Scores in head trauma patients. This was a prospective study conducted with 80 trauma patients presenting to the Emergency Department. Patients were divided into four groups. The first group consisted of patients with general body trauma, but no head trauma. The second group had minor head trauma. The third group had moderate head trauma, and the fourth group had severe head trauma. The relationship between subjects' admission NSE levels and admission and discharge Glasgow Coma Scores (GCS) and Glasgow Outcome Scores (GOS) 1 month later was examined. A receiver operating characteristic (ROC) analysis was performed using a serum NSE cutoff level of 20.52 ng/mL and a GOS of 3 or less as the definition of poor neurologic outcome. There was a significant difference in the NSE levels between group 1 (general trauma) and group 3 (moderate head trauma). There was also a statistically significant difference in NSE levels between group 1 (general trauma) and group 4 (severe head trauma) (p < 0.05). There was a statistically significant inverse relationship between NSE levels and GOS as determined within groups 3 (moderate) and 4 (severe head trauma) (p < 0.05). When NSE levels were compared with admission GCS, it was found that GCS fell as NSE levels rose. There was no significant correlation between NSE and GCS within groups 3 (moderate) or 4 (severe). There was a statistically significant correlation within group 2 (mild) (p < 0.05). By ROC analysis, serum NSE was 87% sensitive and 82.1% specific in predicting poor neurologic outcome in the study patients. The area under the curve was 0.931. This study shows that initial serum NSE levels in moderate and severe head trauma patients correlate inversely with GOS 1 month later, but only within the moderate and severe head trauma groups. However, serum NSE was 87% sensitive and 82.1% specific in predicting poor neurologic outcome in all of the study patients. This derived cutoff value now needs to be prospectively validated.
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ABSTRACT: Several studies have suggested that neuron-specific enolase (NSE) in serum may be a biomarker of traumatic brain injury. However, whether serum NSE levels correlate with outcomes remains unclear. The purpose of this review was to evaluate the prognostic value of serum NSE protein after traumatic brain injury.PLoS ONE 09/2014; 9(9):e106680. DOI:10.1371/journal.pone.0106680 · 3.53 Impact Factor
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ABSTRACT: There is a lack of reliable serum biomarkers for routine use in the diagnostic workup of people with traumatic brain injury. Multiple biomediators and biomarkers have been described in the pertinent literature in recent years; however, only a few candidate molecules have been associated with high sensitivity and high specificity for risk stratification and outcome prediction after traumatic brain injury. This review was designed to provide an overview of the state of the art regarding established serum biomarkers in the field and to outline future directions of investigation.Southern Medical Journal 04/2014; 107(4):248-255. DOI:10.1097/SMJ.0000000000000086 · 1.12 Impact Factor
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ABSTRACT: Developing insight into which factors determine prognosis after traumatic brain injury (TBI) is useful for clinical practice, research, and policy making. Several steps can be identified in prediction research: univariate analysis, multivariable analysis, and the development of prediction models. For each step, several methodological issues should be considered, such as selection/coding of predictors and dealing with missing data. "Traditional" predictors include demographic factors (age), type of injury, clinical severity, second insults, and the presence of structural abnormalities on neuroimaging. In combination, these predictors can explain approximately 35% of the variance in outcome in populations with severe and moderate TBI. Novel and emerging predictors include genetic constitution, biomarkers, and advanced magnetic resonance (MR) imaging. To estimate prognosis for individual patients reliably, multiple predictors need to be considered jointly in prognostic models. Two prognostic models for use in TBI, developed upon large patient numbers, have been extensively validated externally: the IMPACT and CRASH prediction models. Both models showed good performance in validations across a wide range of settings. Importantly, these models were developed not only for mortality but also for functional outcome. Prognostic models can be used for providing information to relatives of individual patients, for resource allocation, and to support decisions on treatment. At the group level, prognostic models aid in the characterization of patient populations, are important to clinical trial design and analysis, and importantly, can serve as benchmarks for assessing quality of care. Continued development, refinement, and validation of prognostic models for TBI is required and this should become an ongoing process. © 2015 Elsevier B.V. All rights reserved.Handbook of Clinical Neurology 01/2015; 128:455-74. DOI:10.1016/B978-0-444-63521-1.00029-7