***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: BACKGROUND Interleukin ( IL ) 1 is a proinflammatory cytokine that has been identified as an important mediator of neurodegeneration induced by ischemia or traumatic brain injury . Accumulating evidence to date has suggested that the major cytokine contributing to neurodegeneration after head injury is IL-1beta rather than IL-1alpha ; however , there is no sufficient data regarding IL-1alpha in literature , and there may be an association between IL1A gene polymorphism and outcome after head injury . METHODS We performed a prospect i ve clinical study and included a recruited series of 71 patients who had head injury and were admitted to our neurosurgical unit . Severity of initial injury was assessed by the Glasgow Coma Scale . Outcome at 6 months after injury was assessed by means of the Glasgow Outcome Score . Interleukin 1alpha genotypes were determined from blood sample s by st and ard methods . RESULTS Of 40 patients with IL1A*2 , 18 ( 45 % ) had an unfavorable outcome ( dead , vegetative state , or severe disability ) compared with 7 ( 22.5 % ) of 31 without IL1A*2 ( P = .08 ) . CONCLUSION Our findings show that there is no genetic association between IL1A gene polymorphism and outcome after head injury . Further clinical studies should be design ed to confirm and further evaluate these findings BACKGROUND Diffuse axonal injury is a common consequence of traumatic brain injury that frequently involves the parasagittal white matter , corpus callosum , and brainstem . OBJECTIVE To examine the potential of diffusion tensor tractography in detecting diffuse axonal injury at the acute stage of injury and predicting long-term functional outcome . DESIGN Tract-derived fiber variables were analyzed to distinguish patients from control subjects and to determine their relationship to outcome . SETTING Inpatient traumatic brain injury unit . PATIENTS From 2005 to 2006 , magnetic resonance images were acquired in 12 patients approximately 7 days after injury and in 12 age- and sex-matched controls . MAIN OUTCOME MEASURES Six fiber variables of the corpus callosum , fornix , and peduncular projections were obtained . Glasgow Outcome Scale-Extended scores were assessed approximately 9 months after injury in 11 of the 12 patients . RESULTS At least 1 fiber variable of each region showed diffuse axonal injury-associated alterations . At least 1 fiber variable of the anterior body and splenium of the corpus callosum correlated significantly with the Glasgow Outcome Scale-Extended scores . The predicted outcome scores correlated significantly with actual scores in a mixed-effects model . CONCLUSION Diffusion tensor tractography-based quantitative analysis at the acute stage of injury has the potential to serve as a valuable biomarker of diffuse axonal injury and predict long-term outcome Numerous studies addressing different methods of head injury prognostication have been published . Unfortunately , these studies often incorporate different head injury prognostication models and study population s , thus making direct comparison difficult , if not impossible . Furthermore , newer artificial intelligence tools such as machine learning methods have evolved in the field of data analysis , alongside more traditional methods of analysis . This study targets the development of a set of integrated prognostication model combining different classes of outcome and prognostic factors . Method ologies such as discriminant analysis , logistic regression , decision tree , Bayesian network , and neural network were employed in the study . Several prognostication models were developed using prospect ively collected data from 513 severe closed head-injured patients admitted to the Neurocritical Unit at National Neuroscience Institute of Singapore , from April 1999 to February 2003 . The correlation between prognostic factors at admission and outcome at 6 months following injury was studied . Overfitting error , which may falsely distinguish different outcomes , was compared graphically . Tenfold cross-validation technique , which reduces overfitting error , was used to vali date outcome prediction accuracy . The overall prediction accuracy achieved ranged from 49.79 % to 81.49 % . Consistently high outcome prediction accuracy was seen with logistic regression and decision tree . Combining both logistic regression and decision tree models , a hybrid prediction model was then developed . This hybrid model would more accurately predict the 6-month post-severe head injury outcome using baseline admission parameters Background : Subjects with moderate head injury are a particular challenge for the emergency physician . They represent a heterogeneous population of subjects with large variability in injury severity , clinical course and outcome . We aim ed to determine the early predictors of outcome of subjects with moderate head injury admitted to an Emergency Department ( ED ) of a general hospital linked via telemedicine to the Regional Neurosurgical Centre . Patients and methods : We review ed , prospect ively , 12 675 subjects attending the ED of a General Hospital between 1999 and 2005 for head injury . A total of 309 cases ( 2.4 % ) with an admission Glasgow Coma Scale ( GCS ) 9–13 were identified as having moderate head injury . The main outcome measure was an unfavourable outcome at 6 months after injury . The predictive value of a model based on main entry variables was evaluated by logistic regression analysis . Findings : 64.7 % of subjects had a computed tomographic scan that was positive for intracranial injury , 16.5 % needed a neurosurgical intervention , 14.6 % had an unfavourable outcome at 6 months ( death , permanent vegetative state , permanent severe disability ) . Six variables ( basal skull fracture , subarachnoid haemorrhage , coagulopathy , subdural haematoma , modified Marshall category and GCS ) predicted an unfavourable outcome at 6 months . This combination of variables predicts the 6-month outcome with high sensitivity ( 95.6 % ) and specificity ( 86.0 % ) . Interpretation : A group of selected variables proves highly accurate in the prediction of unfavourable outcome at 6 months , when applied to subjects admitted to an ED of a General Hospital with moderate head injury OBJECTIVES To identify the demographic and clinical variables related to the duration of posttraumatic amnesia after severe closed head injury ; to evaluate the usefulness of posttraumatic amnesia duration in predicting outcome at the time of hospital discharge and at 6 months after injury . SETTING Four clinical centers located in primary care hospitals . PATIENTS Three hundred fourteen severely injured subjects aged 16 years or older who did not have trauma as a result of a penetrating injury and came out of coma before hospital discharge . INTERVENTIONS Approximately half of the subjects were administered phenytoin sodium for some period after termination of coma ; 17 % were administered dexamethasone and 41 % morphine sulfate . MAIN OUTCOME MEASURES Galveston Orientation and Amnesia Test scores defined the duration of posttraumatic amnesia . The Glasgow Outcome Scale was used to grade outcome at the time of hospital discharge and at 6 months . RESULTS Older age , low initial Glasgow Coma Scale score , nonreactive pupil(s ) , coma duration , and use of phenytoin were associated with a longer duration of posttraumatic amnesia . Poor pupillary response , time in coma , and duration of posttraumatic amnesia and use of phenytoin was predictive of the 6-month outcome . CONCLUSIONS The results support the prognostic usefulness of prospect ively measuring duration of posttraumatic amnesia after termination of coma . Pending replication , our findings suggest that posttraumatic amnesia duration may be a useful surrogate outcome measure for clinical trials involving interventions for acute head injury The early prediction of outcome after traumatic brain injury ( TBI ) is important for several purpose s , but no prognostic models have yet been developed with proven generalizability across different setting s. The objective of this study was to develop and vali date prognostic models that use information available at admission to estimate 6-month outcome after severe or moderate TBI . To this end , this study evaluated mortality and unfavorable outcome , that is , death , and vegetative or severe disability on the Glasgow Outcome Scale ( GOS ) , at 6 months post-injury . Prospect ively collected data on 2269 patients from two multi-center clinical trials were used to develop prognostic models for each outcome with logistic regression analysis . We included seven predictive characteristics-age , motor score , pupillary reactivity , hypoxia , hypotension , computed tomography classification , and traumatic subarachnoid hemorrhage . The models were vali date d internally with bootstrapping techniques . External validity was determined in prospect ively collected data from two relatively unselected surveys in Europe ( n = 796 ) and in North America ( n = 746 ) . We evaluated the discriminative ability , that is , the ability to distinguish patients with different outcomes , with the area under the receiver operating characteristic curve ( AUC ) . Further , we determined calibration , that is , agreement between predicted and observed outcome , with the Hosmer-Lemeshow goodness-of-fit test . The models discriminated well in the development population ( AUC 0.78 - 0.80 ) . External validity was even better ( AUC 0.83 - 0.89 ) . Calibration was less satisfactory , with poor external validity in the North American survey ( p < 0.001 ) . Especially , observed risks were higher than predicted for poor prognosis patients . A score chart was derived from the regression models to facilitate clinical application . Relatively simple prognostic models using baseline characteristics can accurately predict 6-month outcome in patients with severe or moderate TBI . The high discriminative ability indicates the potential of this model for classifying patients according to prognostic risk The objective of this report is to describe the design and content of the International Mission for Prognosis And Clinical Trial ( IMPACT ) data base of traumatic brain injury which contains the complete data set from most clinical trials and organized epidemiologic studies conducted over the past 20 years . This effort , funded by the U.S. National Institutes of Health , has led to the accumulation thus far of data from 9205 patients with severe and moderate brain injuries from eight r and omized placebo controlled trials and three observational studies . Data relevant to the design and analysis of pragmatic Phase III clinical trials , including pre-hospital , admission , and post-resuscitation assessment s , information on the acute management , and short- and long-term outcome were merged into a top priority data set ( TPDS ) . The major emphasis during the first phase of study is on information from time of injury to post-resuscitation and outcome at 6 months thereby providing a unique re source for prognostic analysis and for studies aim ed at optimizing the design and analysis of Phase III trials in traumatic brain injury OBJECTIVE To investigate the value of transcranial Doppler ( TCD ) ultrasonography in evaluating the outcome of severe traumatic brain injury and to correlate the TCD values with intracranial pressure ( ICP ) and cerebral perfusion pressure ( CPP ) monitoring . METHODS A prospect i ve study was conducted to evaluate the contribution of TCD ultrasonography to neurological outcome in a series of 96 severe traumatic brain injury patients . The quantitative variables of TCD ultrasonography included the mean blood flow velocity of the middle cerebral artery ( MCA ) and pulsatility index within the first 24 hours of admission . The ICP and CPP values were a lso recorded . Outcome in 6 months postinjury was evaluated using the Glasgow Outcome Scale ( GOS 4 - 5 was considered as " good " and GOS 1 - 3 as " poor " ) . RESULTS The mean blood flow velocity of the MCA was larger than 40 cm/s in 30 ( 51 % ) patients with good outcome whereas it was less than 40 cm/s in 27 ( 73 % ) patients with poor outcome ( P<0.025 ) . The mean PI in cases of good outcome ( 34 patients , 57 % ) was lower than 1.5 whereas in poor outcome ( 30 patients , 83 % ) was higher than 1.5 ( P<0.001 ) . The correlations of ICP and CPP to pulsatility index were statistically significant ( P<0.01 ) . CONCLUSIONS TCD ultrasonography is valid in predicting the patient 's outcome of 6 months and correlates significantly with ICP and CPP values when it is performed in the first 24 hours of severe traumatic brain injury The authors conducted a study to determine the value of transcranial Doppler ( TCD ) ultrasonography in evaluating the outcome of severely head injured patients and to correlate the TCD values with those obtained from intracranial pressure ( ICP ) and cerebral perfusion pressure ( CPP ) monitoring . The authors conducted a prospect i ve study of 125 patients with severe head injury ( Glascow Coma Scale scores of less than 9 ) who underwent TCD ultrasonography according to the st and ard technique of insonating the middle cerebral artery ( MCA ) and measuring the mean blood flow velocity and pulsatility index within the first 24 hours of admission . The ICP and CPP values , as well as other clinical , analytical , and neuroimaging data , were also recorded . After 6 months , outcome was evaluated using the Glasgow Outcome Scale . Moderate disability and complete recovery were considered " good " outcome ; death , vegetative state , and severe disability were considered " poor . " In 67 patients ( 54 % ) good outcome was demonstrated whereas in 58 ( 46 % ) it was poor . The mean blood flow velocity of the MCA in patients with good outcome was 44 cm/second ; in those with poor outcomes it was 36 cm/second ( p < 0.003 ) . The mean PI in cases of good outcome was 1 whereas in poor outcome was 1.56 ( p < 0.0001 ) . The correlations of ICP and CPP to PI were statistically significant ( r2 = 0.6 ; p < 0.0001 ) . When performed in the first 24 hours of severe head injury , TCD ultrasonography is valid in predicting the patient 's outcome at 6 months and correlates significantly with ICP and 
    Output:
    
Strong evidence for predicting outcome at 6 months was found for the Glasgow Coma Scale ( GCS ) , GCS admission , motor score , midline shift on computed tomography scan , subdural haematoma and pulsatility index .
Strong evidence of no association was found for gender and intraventricular haemorrhage .
For other determinants , inconclusive or no evidence was found .
GCS , GCS on admission , motor score , midline shift , subdural haematoma and pulsatility index predicted outcome 6 months after traumatic brain injury .
Gender and intraventricular haemorrhage did not have predictive value