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Background: Traumatic brain injury (TBI) is a critical health problem with various comorbidities and socioeconomic consequences. Tending to increase in recent decades, TBI results in more cases of consciousness disorders including vegetative state (VS)/minimally conscious state (MCS). However, no definite or effective treatment still exists for these conditions. The aim of this article is to study the effects of zolpidem in patients with VS caused by TBI by using brain perfusion single-photon emission computed tomography (SPECT). Materials and Methods: This was a prospective clinical trial on a cohort of patients with VS. We evaluated the TBI database to find VS/MCS patients, between the ages of 20 and 65 years. We received written consent from their family members prior to enrollment and compared their clinical status and brain perfusion SPECT prior and after 2 weeks of zolpidem therapy. Results: Among the 12 patients included in this study, six patients changed to MCS after 2 weeks. Comparison of their motor score, revealed a statistically significant difference (2.08 vs. 3.75, P = 0.007, respectively). None of the quantitative or qualitative brain perfusion parameters showed any differences after zolpidem therapy. However, the perfusion pattern, with focal or multifocal cortical defects, was significantly more prevalent in the responder group (five patients vs. one patient, P = 0.015). Conclusion: Zolpidem therapy may improve consciousness levels and motor function in a considerable portion of VS patients with TBI. This study showed that the presence of focal brain perfusion defect can predict response to zolpidem. [ABSTRACT FROM AUTHOR]

Background: Large amounts of information have called for increased computational complexity. Data dimension reduction is therefore critical to preliminary analysis. In this research, four variable selection (VS) methods are compared to obtain the important variables in predicting the prognosis of traumatic brain injury (TBI) patients. Materials and Methods: In a retrospective follow up study, 741 TBI patients who were hospitalized for at least 2 days and had a Glasgow Coma Scale score of at least one were followed. Their clinical data recorded during intensive care unit (ICU) admission and eight category extended GOS conditions 6 months after discharge were utilized here. Two filter and two wrapper based VS methods were applied for comparison. A support vector machine (SVM) classifier was then used, and the sensitivity, specificity, accuracy, and the area under the receiver characteristic curve (AUC) values were calculated. Results: Theoretically, the variables selected by sequential forward selection (SFS) method would better predict the prognosis (AUC = 0.737, 95% confidence interval [0.701, 0.772], specificity = 89.2%, sensitivity = 58.9% and accuracy = 79.1%) than the others. Genetic algorithm (GA), minimum redundancy maximum relevance (MRMR), and mutual information method were in the next orders, respectively. Conclusion: The use of an SVM classifier on optimal subsets given by GA and SFS reveals that wrapper based methods perform better than filter based methods in our data set, although all selected subsets, except for the MRMR, were clinically accepted. In addition, for prognosis prediction of TBI patients, a small subset of clinical records during ICU admission is enough to achieve an accepted accuracy. [ABSTRACT FROM AUTHOR]

Objective: To investigate the determinants of outcome in patients with traumatic brain injury (TBI) undergoing decompressive craniectomy (DC) in a large level I trauma center in southern Iran., Methods: This retrospective cross-sectional study was conducted during an 18-month period from 2013 to 2014 in Shahid Rajaei hospital, a Level I trauma center in Southern Iran. Patients with TBI who had undergone DC were included and the medical charts were reviewed regarding demographics, clinical, radiological and outcome characteristics. The outcome was determined by extended Glasgow outcome scale (GOS-E) after one year of surgery. The variables were compared between those with favorable and unfavorable outcome to investigate the outcome determinants., Results: Overall 142 patients with mean age of 34.8 ± 15.5 (ranging from 15 to 85) years were included. There were 127 (89.4%) men and 15 (10.6%) women among the patients. After 1-year, the mortality rate was 58 (40.8%) and 8 (5.6%) patients were persistent vegetative state. The final outcome was found to be unfavorable in 77 (54.2%) patients.  Unfavorable outcome was associated with lower GCS on admission ( p<0.001 ) as well as occurrence of postoperative hydrocephalus ( p=0.011 ). Formation of the postoperative subdural hygroma after the operation was found to be associated with favorable outcome ( p=0.019 )., Conclusion: DC in patients with TBI is associated with favorable outcome in most of them. On admission GCS, postoperative hydrocephalus and presence of postoperative subdural hygroma are among the important predictors of outcome in TBI patients undergoing DC., Competing Interests: There isn’t any conflict of interest to be declared regarding the manuscript.

Background: Generally, traumatic brain injury (TBI) patients do not have a stable condition, particularly after the first week of TBI. Hence, indicating the attributes in prognosis through a prediction model is of utmost importance since it helps caregivers with treatment-decision options, or prepares the relatives for the most-likely outcome., Objectives: This study attempted to determine and order the attributes in prognostic prediction in TBI patients, based on early clinical findings. A hybrid method was employed, which combines a decision tree (DT) and an artificial neural network (ANN) in order to improve the modeling process., Methods: The DT approach was applied as the initial analysis of the network architecture to increase accuracy in prediction. Afterwards, the ANN structure was mapped from the initial DT based on a part of the data. Subsequently, the designed network was trained and validated by the remaining data. 5-fold cross-validation method was applied to train the network. The area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, and accuracy rate were utilized as performance measures. The important attributes were then determined from the trained network using two methods: change of mean squared error (MSE), and sensitivity analysis (SA)., Results: The hybrid method offered better results compared to the DT method. The accuracy rate of 86.3 % vs. 82.2 %, sensitivity value of 55.1 % vs. 47.6 %, specificity value of 93.6 % vs. 91.1 %, and the area under the ROC curve of 0.705 vs. 0.695 were achieved for the hybrid method and DT, respectively. However, the attributes' order by DT method was more consistent with the clinical literature., Conclusions: The combination of different modeling methods can enhance their performance. However, it may create some complexities in computations and interpretations. The outcome of the present study could deliver some useful hints in prognostic prediction on the basis of early clinical findings for TBI patients.

Objective: To determine the effects of application of anti-adhesive films (OrthoWrap™) in traumatic decompressive craniectomy on prevention of adhesion formation and facilitation of subsequent cranioplasty., Methods: This was a retrospective cohort study being performed in ShahidRajaei hospital (Shiraz Level I trauma center) during a 12-month period (from March 2012 to April 2013) including 93 patients undergoing traumatic decompressivecraniectomy.Patients who received OrthoWrap™ during the initial craniectomy (n=44) were compared to those who did not (n=49). Two study groups were matched regarding the baseline characteristics. The perioperative indices including the surgical time, amount of bleeding, transfusion and 6-month Glasgow Outcome Scale (GOS) were compared between two study groups., Results: There was no significant difference between two study groups regarding the baseline characteristics. We found that the cranioplasty duration (113.3±33.2 vs. 146.9±34.9 minutes; p<0.001) and amount of intraoperative bleeding (182.1±98.3 vs. 270.6±77.6 mL; p=0.043) was significantly lower in those who had OrthoWrap™ compared to control group. The final GCS (p=0.052) as well as GOSE (p=0.653) was comparable between groups. The infection rate was comparable between two study groups (p=0.263)., Conclusion: Application of OrthoWrap™ during decompressive craniectomy in those with severe traumatic brain injury is associated with shorter duration of operation and less intraoperative bleeding in subsequent cranioplasty. Infection rate and neurologic outcome was comparable between study groups.

Deep vein thrombosis (DVT) and pulmonary embolism (PTE) are known as venous thromboembolism (VTE). DVT occurs when a thrombus (a blood clot) forms in deep veins of the body, usually in the lower extremities. It can cause swelling or leg pain, but sometimes may occur with no symptoms. Awareness of DVT is the best way to prevent the VTE. Patients with trauma are at increased risk of DVT and subsequent PE because of coagulopathy in patients with multiple trauma, DVT prophylaxis is essential but the VTE prophylaxis strategy is controversial for the trauma patients. The risk factors for VTE includes pelvic and lower extremity fractures, and head injury.

Objective: To determine the diagnostic value of serum white blood cell (WBC) count, fever (>38˚C) and WBC rise (>10%) for bacterial meningitis in patients with severe traumatic brain injury (TBI)., Method: This cross-sectional study was conducted in Shahid Rajaei hospital affiliated with Shiraz University of Medical Sciences during a 1-year period from 2013 to 2014. We included consecutively all the patients with severe TBI admitted to our center during the study period who were febrile (>38˚C orally) and underwent lumbar puncture (LP) and analysis and culture of cerebrospinal fluid (CSF). Laboratory analysis of CSF and blood were performed within 2 hours of LP. CSF culture was considered the gold standard for diagnosis of bacterial meningitis. The sensitivity, specificity, positive and negative predictive value (PPV, NPV) of peripheral blood WBC count, fever (>38˚C) and WBC rise (>10%) was determined according to the CSF culture., Results: Overall we included242 consecutive patients with severe TBI. The mean age of the participants was 32.8 ± 17.4 years. Acinetobacter was the most common organism found in the CSF cultures. The sensitivity and specificity of peripheral WBC count (>10,000)was 48.4% (95% CI: 0.42-0.56) and 47% (95% CI: 0.37-0.58) respectively. The PPV and NPV was 13.1% (95% CI: 0.33-0.52) and 84.8% (95% CI: 0.42-0.61), respectively. The AUC for WBC count was 0.478 (95% CI: 0.37-0.58) indicating low accuracy for the diagnosis of bacterial meningitis. The AUC for WBC rise (>10%) and temperature >38˚C was0.460 (95% CI: 0.351-0.569) and 0.517 (95% CI: 0.410-0.624) respectively, both indicating low accuracy for diagnosis of bacterial meningitis., Conclusion: The results of the current study indicates that peripheral blood leukocyte count, fever (>38˚C) and WBC rise (>10%) is a non-reliable marker for diagnosis of bacterial meningitis in patients with severe TBI.