Intensive glycemic control in traumatic brain injury: what is the ideal glucose range?

Intensive glycemic control has become standard practice. Existing data, however, suggest this practice may have adverse consequences for traumatic brain injury. The recent paper by Meier and colleagues suggests that intensive glycemic control may be deleterious. The present article explores existing literature surrounding this controversy, and outlines the literature that raises concern. Finally, I suggest an alternative course of action that may enable control of glucose in an optimal range

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction.

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome

Multiplex Networks to Characterize Seizure Development in Traumatic Brain Injury Patients

Traumatic brain injury (TBI) may cause secondary debilitating problems, such as post-traumatic epilepsy (PTE), which occurs with unprovoked recurrent seizures, months or even years after TBI. Currently, the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) has been enrolling moderate-severe TBI patients with the goal to identify biomarkers of epileptogenesis that may help to prevent seizure occurrence and better understand the mechanism underlying PTE. In this work, we used a novel complex network approach based on segmenting T1-weighted Magnetic Resonance Imaging (MRI) scans in patches of the same dimension (network nodes) and measured pairwise patch similarities using Pearson's correlation (network connections). This network model allowed us to obtain a series of single and multiplex network metrics to comprehensively analyze the different interactions between brain components and capture structural MRI alterations related to seizure development. We used these complex network features to train a Random Forest (RF) classifier and predict, with an accuracy of 70 and a 95% confidence interval of [67, 73%], which subjects from EpiBioS4Rx have had at least one seizure after a TBI. This complex network approach also allowed the identification of the most informative scales and brain areas for the discrimination between the two clinical groups: seizure-free and seizure-affected subjects, demonstrating to be a promising pilot study which, in the future, may serve to identify and validate biomarkers of PTE

Comparison of 3-Factor Prothrombin Complex Concentrate and Low-Dose Recombinant Factor VIIa for Warfarin Reversal

INTRODUCTION: Prothrombin complex concentrate (PCC) and recombinant Factor VIIa (rFVIIa) have been used for emergent reversal of warfarin anticoagulation. Few clinical studies have compared these agents in warfarin reversal. We compared warfarin reversal in patients who received either 3 factor PCC (PCC3) or low-dose rFVIIa (LDrFVIIa) for reversal of warfarin anticoagulation. METHODS: Data were collected from medical charts of patients who received at least one dose of PCC3 (20 units/kg) or LDrFVIIa (1000 or 1200 mcg) for emergent warfarin reversal from August 2007 to October 2011. The primary end-points were achievement of an INR 1.5 or less for efficacy and thromboembolic events for safety. RESULTS: Seventy-four PCC3 and 32 LDrFVIIa patients were analyzed. Baseline demographics, reason for warfarin reversal, and initial INR were equivalent. There was no difference in the use of vitamin K or fresh frozen plasma. More LDrFVIIa patients achieved an INR of 1.5 or less (71.9% vs. 33.8%, p =0.001). The follow-up INR was lower after LDrFVIIa (1.25 vs. 1.75, p < 0.05) and the percent change in INR was larger after LDrFVIIa (54.1% vs. 38.8%, p = 0.002). There was no difference in the number of thromboembolic events (2 LDrFVIIa vs. 5 PCC3, p = 1.00), mortality, length of hospital stay, or cost. CONCLUSIONS: Based on achieving a goal INR of 1.5 or less, LDrFVIIa was more likely than PCC3 to reverse warfarin anticoagulation. Thromboembolic events were equivalent in patients receiving PCC3 and LDrFVIIa

Personality (at Intrapsychic and Interpersonal Level) Associated With Quality of Life in Patients With Cancer (Lung and Colon)

The objective of this study was to determine the association of quality of life (QoL) and intrapsychic and interpersonal behaviors (Structural Analysis of Social Behavior [SASB]) of patients with cancer (lung: n = 88; age 62.8 ± 10.1; colon: n = 56; age 60.1 ± 11.4). Personality described by SASB clusters (Cls): SASB-Questionnaire; QoL tests: FACT_G and QLQ-C30. Patients with lung cancer (n = 88; age 62.8 ± 10.1) and colon cancer (n = 56; age 60.1 ± 11.4; all stages of severity). Multiple regression analyses. Multiple linear regression: dependent variable: FACT_G; covariates: physical functioning, cognitive functioning, SASB-Cl3-50°, SASB-Cl6-50°. Analysis of variance and t test confirm validity of the model (P &lt; .001). SASB-Cl3 with FACT_G (P = .034); SASB-Cl6 with FACT_G (P = .002); age with FACT_G (P = .018); physical functioning with FACT_G (P &lt; .001); cognitive functioning with FACT_G (P &lt; .001). Personality traits such as self-critical and oppressive behaviors, low capacity for self-esteem, physical and cognitive functioning, and age (a higher age determines a better QoL) strongly determine QoL in patients with lung and colon cancer. This may suggest areas of therapeutic intervention

Analyses of cerebral microdialysis in patients with traumatic brain injury: relations to intracranial pressure, cerebral perfusion pressure and catheter placement

<p>Abstract</p> <p>Background</p> <p>Cerebral microdialysis (MD) is used to monitor local brain chemistry of patients with traumatic brain injury (TBI). Despite an extensive literature on cerebral MD in the clinical setting, it remains unclear how individual levels of real-time MD data are to be interpreted. Intracranial pressure (ICP) and cerebral perfusion pressure (CPP) are important continuous brain monitors in neurointensive care. They are used as surrogate monitors of cerebral blood flow and have an established relation to outcome. The purpose of this study was to investigate the relations between MD parameters and ICP and/or CPP in patients with TBI.</p> <p>Methods</p> <p>Cerebral MD, ICP and CPP were monitored in 90 patients with TBI. Data were extensively analyzed, using over 7,350 samples of complete (hourly) MD data sets (glucose, lactate, pyruvate and glycerol) to seek representations of ICP, CPP and MD that were best correlated. MD catheter positions were located on computed tomography scans as pericontusional or nonpericontusional. MD markers were analyzed for correlations to ICP and CPP using time series regression analysis, mixed effects models and nonlinear (artificial neural networks) computer-based pattern recognition methods.</p> <p>Results</p> <p>Despite much data indicating highly perturbed metabolism, MD shows weak correlations to ICP and CPP. In contrast, the autocorrelation of MD is high for all markers, even at up to 30 future hours. Consequently, subject identity alone explains 52% to 75% of MD marker variance. This indicates that the dominant metabolic processes monitored with MD are long-term, spanning days or longer. In comparison, short-term (differenced or Δ) changes of MD vs. CPP are significantly correlated in pericontusional locations, but with less than 1% explained variance. Moreover, CPP and ICP were significantly related to outcome based on Glasgow Outcome Scale scores, while no significant relations were found between outcome and MD.</p> <p>Conclusions</p> <p>The multitude of highly perturbed local chemistry seen with MD in patients with TBI predominately represents long-term metabolic patterns and is weakly correlated to ICP and CPP. This suggests that disturbances other than pressure and/or flow have a dominant influence on MD levels in patients with TBI.</p

Patient-Tailored Connectomics Visualization for the Assessment of White Matter Atrophy in Traumatic Brain Injury

Available approaches to the investigation of traumatic brain injury (TBI) are frequently hampered, to some extent, by the unsatisfactory abilities of existing methodologies to efficiently define and represent affected structural connectivity and functional mechanisms underlying TBI-related pathology. In this paper, we describe a patient-tailored framework which allows mapping and characterization of TBI-related structural damage to the brain via multimodal neuroimaging and personalized connectomics. Specifically, we introduce a graphically driven approach for the assessment of trauma-related atrophy of white matter connections between cortical structures, with relevance to the quantification of TBI chronic case evolution. This approach allows one to inform the formulation of graphical neurophysiological and neuropsychological TBI profiles based on the particular structural deficits of the affected patient. In addition, it allows one to relate the findings supplied by our workflow to the existing body of research that focuses on the functional roles of the cortical structures being targeted. A graphical means for representing patient TBI status is relevant to the emerging field of personalized medicine and to the investigation of neural atrophy