Predictive Factors of Survival and 6-Month Favorable Outcome of Very Severe Head Trauma Patients; a Historical Cohort Study

Introduction: Very severe head trauma cases, defined as Glasgow Coma Scale (GCS) scores of less than 6, have a higher mortality rate and poorer outcome. The purpose of this study was to recognize factors associated with survival and 6-month favorable outcome of very severe head trauma patients presenting to emergency department. Methods: In this historical cohort study, the authors retrospectively reviewed medical records of head trauma patients who were admitted to the emergency department with post-resuscitation GCS scores of less than 6. Both univariate and multivariate analyses were used to test the association between various parameters with survival and 6-month outcome. Results: 103 cases with the mean age of 39 ± 16.5 years were studied (80% male). The overall survival rate was 41.7% and the rate of 6-month favorable outcome was 28.2%. In multivariate analysis, brisk pupil light reaction on admission and patent basal cistern on brain computed tomography (CT) scan were significant factors associated with both survival (OR 5.20, 95% CI 1.57-17.246, p = 0.007 and OR 3.65, 95% CI 1.22-10.91, p=0.02 respectively) and favorable outcome (OR 4.07, 95% CI 1.35-12.24, p=0.01 and OR 3.54, 95% CI 1.22-10.26, p 0.02), respectively. Conclusion: Based on the results of present study, the survival rate of patients with very severe head trauma (GCS < 6) was 41.7%. The strong predictors of survival and 6-month favorable outcome of these patients were brisk pupillary reactivity and patent cistern on brain CT scan. It seems that very severe head trauma patients still have a reasonable chance to survive and aggressive management should be continued

Comparison of intracranial pressure prediction in hydrocephalus patients among linear, non-linear, and machine learning regression models in Thailand

Background Hydrocephalus (HCP) is one of the most significant concerns in neurosurgical patients because it can cause increased intracranial pressure (ICP), resulting in mortality and morbidity. To date, machine learning (ML) has been helpful in predicting continuous outcomes. The primary objective of the present study was to identify the factors correlated with ICP, while the secondary objective was to compare the predictive performances among linear, non-linear, and ML regression models for ICP prediction. Methods A total of 412 patients with various types of HCP who had undergone ventriculostomy was retrospectively included in the present study, and intraoperative ICP was recorded following ventricular catheter insertion. Several clinical factors and imaging parameters were analyzed for the relationship with ICP by linear correlation. The predictive performance of ICP was compared among linear, non-linear, and ML regression models. Results Optic nerve sheath diameter (ONSD) had a moderately positive correlation with ICP (r=0.530, P<0.001), while several ventricular indexes were not statistically significant in correlation with ICP. For prediction of ICP, random forest (RF) and extreme gradient boosting (XGBoost) algorithms had low mean absolute error and root mean square error values and high R2 values compared to linear and non-linear regression when the predictive model included ONSD and ventricular indexes. Conclusions The XGBoost and RF algorithms are advantageous for predicting preoperative ICP and establishing prognoses for HCP patients. Furthermore, ML-based prediction could be used as a non-invasive method

Development and Deployment of Web Application Using Machine Learning for Predicting Intraoperative Transfusions in Neurosurgical Operations

Background and Aim: Preoperative blood product preparation is a common practice in neurosurgical patients. However, over-requesting of blood is common and leads to the wastage of blood bank resources. Machine learning (ML) is currently one of the novel computational data analysis methods for assisting neurosurgeons in their decision-making process. The objective of the present study was to use machine learning to predict intraoperative packed red cell transfusion. Additionally, a secondary objective focused on estimating the effectiveness of blood utilization in neurosurgical operations. Methods and Materials/Patients: This was a retrospective cohort study of 3,021 patients who had previously undergone neurosurgical operations. Data from the total cohort were randomly divided into a training dataset (N=2115) and a testing dataset (N=906). The supervised ML models of various algorithms were trained and tested with test data using both classification and regression algorithms. Results: Almost all neurosurgical conditions had a cross-match to transfusion ratio of more than 2.5. Support vector machine (SVM) with linear kernel, SVM radial kernel, and random forest (RF) classification had a performance with good AUC of 0.83,0.82, and 0.82, respectively, while RF regression had the lowest root mean squared error and mean absolute error. Conclusion: In almost all neurosurgical surgeries, preoperative overpreparation of blood products was detected. The ML algorithm was proposed as a high-performance method for optimizing blood preparation and intraoperative consumption. Furthermore, ML has the potential to be incorporated into clinical practice as a calculator for the optimal cross-match to transfusion ratio

Effect of the Extent of Resection on Survival Outcome in Glioblastoma: Propensity Score Approach

Objective To evaluate the effectiveness of the extent of resection (EOR) on survival outcome using propensity score-based approaches. Materials and Methods A retrospective cohort study was performed in patients with newly diagnosed glioblastoma. Propensity score matching (PSM) and propensity score regression adjustment were used in the matched and unmatched dataset, respectively. Therefore, the Kaplan-Meier survival curve and Cox's regression analyses were performed to determine the effect of the EOR on survival outcomes. Results One hundred and sixty-eight patients were included for analyzes. The total tumor resection in the unmatched dataset was 22.6% of all cases. Using PSM, incomplete tumor resection had an unfavorable survival outcome when compared with total tumor resection (hazard ratio (HR) 2.92, 95% confidence interval [CI] 1.72–4.94). Additionally, biopsy and partial tumor resection were significantly associated with poor prognosis when compared with total tumor resection using propensity score regression adjustment (HR of biopsy 1.89, 95%CI 1.13–3.16 and HR of partial resection 1.89, 95%CI 1.28–2.80). Conclusions Patients with total tumor resection tend to have a more favorable prognosis than patients with partial tumor resection. The propensity score-based analysis is an alternative approach to evaluate the effect of an intervention that has limitations to perform a randomized controlled trial

Impact of Road Traffic Injury to Pediatric Traumatic Brain Injury in Southern Thailand

Background: Motor vehicle is a major transportation in Southern Thailand as the result of road traffic injury and death. Consequently, severe disability and mortality in pediatric traumatic brain injury (TBI) were observed from traffic accident, particularly motorcycle accident. To identify the risk of intracranial injury in children, the association of treatment outcome with various factors including mechanisms of injury, clinical characteristics, and intracranial pathology can be assessed. Materials and Methods: This was a retrospective study conducted on children, who were younger than 15 years old with TBI and were enrolled from 2004 to 2015. Several clinically relevant issues were reviewed and statistically analyzed. Results: A total of 948 casualties were enrolled. Compared with falling down, the motorcycle accident was significantly associated with intracranial injury (odds ratio 1.73, 95% confidence interval [CI] 1.08–2.76). Other factors associated with intracranial injury were hemiparesis (odds ratio 5.69, 95% CI 1.44–22.36), positive of basal skull fracture signs (odds ratio 15.66, 95% CI 3.44-71.28), and fixed reaction to light of both pupils (odds ratio 5.74, 95% CI 1.71–19.23). Mortality found in thirty cases (3.2%). Furthermore, the risk of death correlated with motorcycle accident (P = 0.02) and severe head injury (P < 0.001). Neurosurgical intervention was not associated with outcome, but severe head injury, hemorrhagic shock, epidural, and subdural hematoma were impact factors. Conclusion: The findings demonstrate road traffic injury, especially motorcycle accident leading to brain injury and death. Prevention program is a necessary key to decrease mortality and disability in pediatric TBI

External Validation of a Clinical Nomogram for Predicting Intracranial Hematoma Following Head Computed Tomography in Pediatric Traumatic Brain Injury

Introduction Over-investigation of head computed tomography (CT) has been observed in children with TBI. Long-term effects from a head CT brain scan have been addressed and those should be balanced. A nomogram is a simple prediction tool that has been reported for predicting intracranial injuries following a head CT of the brain in TBI children in literature. This study aims to validate the performance of the nomogram using unseen data. Additionally, the secondary objective aims to estimate the net benefit of the nomogram by decision curve analysis (DCA)

Molecular Landscape for Malignant Transformation in Diffuse Astrocytoma

Background Malignant transformation (MT) of low-grade gliomas changes dramatically the natural history to poor prognosis. Currently, factors associated with MT of gliomas have been inconclusive, in particular, diffuse astrocytoma (DA). Objective The present study aimed to explore the molecular abnormalities related to MT in the same patients with different MT stages. Methods Twelve specimens from five DA patients with MT were genotyped using next-generation sequencing (NGS) to identify somatic variants in different stages of MT. We used cross-tabulated categorical biological variables and compared the mean of continuous variables to assess for association with MT. Results Ten samples succussed to perform NGS from one male and four females, with ages ranging from 28 to 58 years. The extent of resection was commonly a partial resection following postoperative temozolomide with radiotherapy in 25% of cases. For molecular findings, poly-T-nucleotide insertion in isocitrate dehydrogenase 1 (IDH1) was significantly related to MT as a dose–response relationship (Mann–Whitney's U test, p = 0.02). Also, mutations of KMT2C and GGT1 were frequently found in the present cohort, but those did not significantly differ between the two groups using Fisher's exact test. Conclusion In summary, we identified a novel relationship between poly-T insertion polymorphisms that established the pathogenesis of MT in DA. A further study should be performed to confirm the molecular alteration with more patients

Diagnostic Yield and Complication of Frameless Stereotactic Brain Biopsy

Background: With the advancement of neuronavigation technologies, frameless stereotactic brain biopsy has been developed. Previous studies proved that frameless stereotactic brain biopsy was as effective and safe as frame-based stereotactic brain biopsy. The authors aimed to find the factors associated with diagnostic yield and complication rate of frameless intracranial biopsy. Materials and Methods: Frameless stereotactic brain biopsy procedures, between March 2009 and April 2017, were retrospectively reviewed from medical records including imaging studies. Using logistic regression analysis, various factors were analyzed for association with diagnostic yield and postoperative complications. Results: Eighty-nine frameless stereotactic brain biopsy procedures were performed on 85 patients. The most common pathology was primary central nervous system lymphoma (43.8%), followed by low-grade glioma (15.7%), and high-grade glioma (15%), respectively. The diagnostic yield was 87.6%. Postoperative intracerebral hematoma occurred in 19% of cases; however, it was symptomatic in only one case. The size of the lesion was associated with both diagnostic yield and postoperative intracerebral hematoma complication. Lesions, larger than 3 cm in diameter, were associated with a higher rate of positive biopsy result (P = 0.01). Lesion 3 cm or smaller than 3 cm in diameter, and intraoperative bleeding associated with a higher percentage of postoperative intracerebral hematoma complications (P = 0.01). Conclusions: For frameless stereotactic brain biopsy, the size of the lesion is the essential factor determining diagnostic yield and postoperative intracerebral hematoma complication

Butterfly Tumor of the Corpus Callosum: Clinical Characteristics, Diagnosis, and Survival Analysis

Background: The pathologies implicate the bilateral corpus callosum that builds the butterfly pattern on axial view. These tumors have seldom been investigated for both clinical manifestations and outcome. Objective: The objective of this study was to describe the clinical characteristics and outcomes of the butterfly tumor and to identify the predictive factors associated with survival outcome. Methods: A retrospective study of 50 butterfly tumor was conducted between 2003 and 2016. The clinical characteristics, imaging, and outcome were assessed for the purpose of descriptive analysis. Using the Kaplan–Meier method, the median overall survival of the butterfly tumor was determined. Furthermore, the Cox proportional hazard regression was the estimated hazard ratio for death. Results: Diffuse large B-cell lymphoma was common of butterfly lesions. The mortality rate was 78% and overall median survival time was 16.03 months (95% confidence interval: 14.0–19.8). Using Cox proportional hazards regression, the independent prognostic factors were Karnofsky Performance Status score ≤70, splenium involvement, and butterfly glioblastoma. Conclusions: The butterfly tumor is a poor prognostic disease compared with each histology subgroup. Further molecular investigation is preferable to explore genetic variations associated with these tumors