The Prognostic Value of Neuron-Specific Enolase in Head Trauma Patients

Department of Emergency Medicine, Ordu General Hospital, Ordu, Turkey.
Journal of Emergency Medicine (Impact Factor: 0.97). 05/2008; 38(3):297-301. DOI: 10.1016/j.jemermed.2007.11.032
Source: PubMed


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.

Download full-text


Available from: Ertugrul Cakir, Jun 01, 2015
  • Source
    • "Marker Biological roles Diagnostic Prognostic Injury mechanism Reference s100B Calcium binding protein found in astrocytes and some neuronal cells Lacks specificity, elevated levels found in the serum of multi-trauma patients Poorly related to outcome as measured by return to work (RTW) Suggests astrocyte damage/activation as a cellular sequelae to primary insult, as well as possible BBB disruption Bazarian et al. (2006), Biberthaler et al. (2006), Naeimi et al. (2006), de Kruijk et al. (2001), Metting et al. (2012), Nygren-de Boussard et al. (2004) Found elevated in serum acutely post mTBI Some validity for diagnosis of intracranial lesions (IL) Even highly elevated levels have been shown full recovery NSE Glycolytic enzyme, specific to the cytoplasm of neurons Lacks sensitivity, and specificity; elevated levels found in blood resulting from hemolysis Poor correlation between serum levels and GOS Suggests acute neuronal damage Meric et al. (2010), Naeimi et al. (2006), Berger et al. (2007), de Kruijk et al. (2001) "
    [Show abstract] [Hide abstract]
    ABSTRACT: Traumatic Brain Injury (TBI) is a global health concern. The majority of TBI's are mild, yet our ability to diagnose and treat mild traumatic brain injury (mTBI) is lacking. This deficiency results from a variety of issues including the difficulty in interpreting ambiguous clinically presented symptoms, and ineffective imaging techniques. Thus, researchers have begun to explore cellular and molecular based approaches to improve both diagnosis and prognosis. This has been met with a variety of challenges, including difficulty in relating biological markers to current clinical symptoms, and overcoming our lack of fundamental understanding of the pathophysiology of mTBI. However, recent adoption of high throughput technologies and a change in focus from the identification of single to multiple markers has given just optimism to mTBI research. The purpose of this review is to highlight a number of current experimental peripheral blood biomarkers of mTBI, as well as comment on the issues surrounding their clinical application and utility.
    Full-text · Article · May 2013 · Frontiers in Neurology
  • [Show abstract] [Hide abstract]
    ABSTRACT: The intensive care treatment of patients with severe traumatic brain injury (TBI) must consider local alterations as well as systemic influences. This, in turn, requires broad clinical experience and knowledge to see and comprehend these severely injured patients in their entirety. This not only pertains to patients with additional injuries but is also valid for patients with isolated severe TBI. Only then can we practice a brainoriented therapy. A merely brain-centered therapy carries the risk of inducing extracerebral organ injuries.
    No preview · Chapter · Jan 1970
  • [Show abstract] [Hide abstract]
    ABSTRACT: Bioinformatics techniques to relative solvent accessibility (RSA) prediction are mostly single-stage approaches; they predict solvent accessibility of proteins by taking into account only the information available in amino acid sequences. We propose to use support vector machines (SVMs) as a second stage following the existing single-stage approaches for RSA prediction problem to improve the accuracy. The purpose of the second stage is to capture the contextual relationship of solvent accessibility elements in a neighborhood in determining the solvent accessibility at a particular site. We demonstrate our approach by introducing SVMs to the output of single-stage SVM classifier. Two-stage SVM approach achieves accuracies up to 90.4% and 90.2% on the Manesh dataset of 215 protein structures and the RS126 dataset of 126 nonhomologous globular proteins, respectively, which are better than the highest reported scores on both datasets to date.
    No preview · Conference Paper · Nov 2004
Show more