941 resultados para Blast traumatic brain injury


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BACKGROUND There has been little research on bathroom accidents. It is unknown whether the shower or bathtub are connected with special dangers in different age groups or whether there are specific risk factors for adverse outcomes. METHODS This cross-sectional analysis included all direct admissions to the Emergency Department at the Inselspital Bern, Switzerland from 1 January 2000 to 28 February 2014 after accidents associated with the bathtub or shower. Time, age, location, mechanism and diagnosis were assessed and special risk factors were examined. Patient groups with and without intracranial bleeding were compared with the Mann-Whitney U test.The association of risk factors with intracranial bleeding was investigated using univariate analysis with Fisher's exact test or logistic regression. The effects of different variables on cerebral bleeding were analysed by multivariate logistic regression. RESULTS Two hundred and eighty (280) patients with accidents associated with the bathtub or shower were included in our study. Two hundred and thirty-five (235) patients suffered direct trauma by hitting an object (83.9%) and traumatic brain injury (TBI) was detected in 28 patients (10%). Eight (8) of the 27 patients with mild traumatic brain injuries (GCS 13-15), (29.6%) exhibited intracranial haemorrhage. All patients with intracranial haemorrhage were older than 48 years and needed in-hospital treatment. Patients with intracranial haemorrhage were significantly older and had higher haemoglobin levels than the control group with TBI but without intracranial bleeding (p<0.05 for both).In univariate analysis, we found that intracranial haemorrhage in patients with TBI was associated with direct trauma in general and with age (both p<0.05), but not with the mechanism of the fall, its location (shower or bathtub) or the gender of the patient. Multivariate logistic regression analysis identified only age as a risk factor for cerebral bleeding (p<0.05; OR 1.09 (CI 1.01;1.171)). CONCLUSION In patients with ED admissions associated with the bathtub or shower direct trauma and age are risk factors for intracranial haemorrhage. Additional effort in prevention should be considered, especially in the elderly.

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CYP4F subfamily comprises a group of enzymes that metabolize LTB4 to biologically less active metabolites. These inactive hydroxy products are incapable of chemotaxis and recruitment of inflammatory cells. This has led to a hypothesis that CYP4Fs may modulate inflammatory conditions serving as a signal of resolution. ^ We investigated the regulation of rat CYP4F gene expression under various inflammatory prompts including a bacterial lipopolysaccharide (LPS) treated model system, controlled traumatic brain injury (TBI) model as well as using direct cytokine challenges. CYP4Fs showed an isoform specific response to LPS. The pro-inflammatory cytokines IL-1β, IL-6 and TNF-α produced an overall inductive CYP4F response whereas IL-10, an anti-inflammatory cytokine, suppressed CYP4F gene expression in primary hepatocytes. The molecular mechanism behind IL-6 mediated CYP4F induction was partially STAT3 dependent. ^ An alternate avenue of triggering the inflammatory cascade is TBI, which is known to cause several secondary effects leading to multiorgan dysfunction syndrome. The results from this study elicited that trauma to the brain can produce acute inflammatory changes in organs distant from the injury site. Local production of LTB4 after CNS injury caused mobilization of inflammatory cells such as neutrophils to the lung. In the resolution phase, CYP4F expression increased with time along with the associated activity causing a decline in LTB4 concentration. This marked a significant reduction in neutrophil recruitment to the lung which led to subsequent recovery and repair. In addition, we showed that CYP4Fs are localized primarily in pulmonary endothelium. We speculate that the temporally regulated LTB4 clearance in the endothelium may be a novel target for treatment of pulmonary inflammation following injury. ^ In humans, several CYP4F isoforms have been identified and shown to metabolize LTB4 and other endogenous eicosanoids. However, the specific activity of the recently cloned human CYP4F11 is unknown. In the final part of this thesis, CYP4F11 protein was expressed in yeast in parallel to CYP4F3A. To our surprise, CYP4F11 displayed a different substrate profile than CYP4F3A. CYP4F3A metabolized eicosanoids while CYP4F11 was a better catalyst for therapeutic drugs. Thus, besides their endogenous function in clearing inflammation, CYP4Fs also may play a part in drug metabolism. ^

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Background. Attention Deficit-Hyperactivity Disorder (AD/HD) diagnosis in children and adolescents has been on the rise over the last couple of decades and a multitude of studies have been conducted in an aim to better understand the disease. Literature has explored the role of several factors suspected of contributing to development of the disease, including: prenatal smoking exposures, environmental exposures, and low-birth weight. However, there is very limited reporting of fetal/infant exposure to antidepressants and prescription medications and the long-term behavioral outcomes, namely development of AD/HD. The purpose of this study was to evaluate the relationship between mother's exposure to prescription medications and/or antidepressants around the time of conception, during pregnancy, or while breastfeeding and the development of Attention-Deficit/Hyperactivity Disorder in offspring. Methods. Secondary analysis of data from a case-control study was performed. Exposure histories were collected for the mother and offspring. Data were collected using a secure, confidential, self-report, online survey to evaluate the relationship between antidepressant and/or prescription medication exposure and the development of AD/HD. The period of exposure to these drugs was defined as: around the time of conception, during pregnancy, or while breastfeeding. Cases were defined as a child who had been diagnosed with AD/HD. Controls were defined as a child who had not been diagnosed with AD/HD. Results. Prescription medication and antidepressant medication exposures around the time of conception, during pregnancy, or while breastfeeding were not associated with development of AD/HD. However, traumatic brain injury (OR=2.77 (1.61–4.77)) and preterm birth (OR=1.48 (1.04–2.12)) were identified as potential risk factors. These results support existing literature on AD/HD, but future work must be undertaken to better evaluate fetal/infant medication exposures and long-term behavioral outcomes.^

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Objetivo: Analizar la mortalidad en la Unidad de Cuidados Intensivos (UCI) del Hospital Central de Mendoza y evaluar el valor predictivo de la escala APACHE II (Evaluación Fisiológica Aguda y de Salud Crónica). Material y Método: Se realizó un estudio retrospectivo y observacional de los pacientes ingresados a la Unidad de Cuidados Intensivos del Hospital Central de Mendoza, desde el 01/11/06 hasta el 31/03/08. Se calculó la distribución de sexos y de edades de la muestra, la estadía promedio, principales motivos de ingreso a la UCI y la puntuación APACHE II en las primeras 24 horas de internación. Se calculó la mortalidad esperada y la mortalidad obtenida global y se analizó el coeficiente entre ambas mortalidades. Resultados: Se incluyeron 904 pacientes, 61,82% masculinos y 38,18% femeninos, con una edad media 46 años (±19,36). Estadía promedio en la UCI 8,5 días promedio. El principal motivo de internación fueron los Traumatismos Encéfalocraneanos (TEC) con un 27,7% del total (86% asociados a politraumatismo grave). La mortalidad global obtenida fue del 41,48% vs. 24,08% esperable, con un coeficiente de mortalidad de 1,72 (p<0,0001). Conclusiones: La UCI estudiada presenta por las características de la población asistida un elevado índice de mortalidad global. La mortalidad obtenida fue 72% mayor a la mortalidad esperable según la puntuación APACHE II, demostrando esta Escala un bajo valor predictivo en nuestra UCI. La diferencia entre mortalidades podría parcialmente explicarse por la alta prevalencia de entidades con mortalidades subvaloradas por este modelo pronóstico, como pacientes politraumatizados y neurocríticos. En nuestro estudio, la Escala APACHE II presentó una franca subestimación de la mortalidad en ambas patologías. Sugerimos la realización de un estudio de regresión logística local para determinar un factor de corrección y/o adicionar puntos al valor APACHE II según el diagnóstico de ingreso del paciente. Asimismo, proponemos evaluar el empleo de medidas alternativas para predecir mortalidad, como sistemas de tercera generación (por ejemplo: APACHE III, MPM II y SAPS II).

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Acquired brain injury (ABI) 1-2 refers to any brain damage occurring after birth. It usually causes certain damage to portions of the brain. ABI may result in a significant impairment of an individuals physical, cognitive and/or psychosocial functioning. The main causes are traumatic brain injury (TBI), cerebrovascular accident (CVA) and brain tumors. The main consequence of ABI is a dramatic change in the individuals daily life. This change involves a disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges in neurorehabilitation is to obtain a dysfunctional profile of each patient in order to personalize the treatment. This paper proposes a system to generate a patient s dysfunctional profile by integrating theoretical, structural and neuropsychological information on a 3D brain imaging-based model. The main goal of this dysfunctional profile is to help therapists design the most suitable treatment for each patient. At the same time, the results obtained are a source of clinical evidence to improve the accuracy and quality of our rehabilitation system. Figure 1 shows the diagram of the system. This system is composed of four main modules: image-based extraction of parameters, theoretical modeling, classification and co-registration and visualization module.

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Tradicionalmente, el uso de técnicas de análisis de datos ha sido una de las principales vías para el descubrimiento de conocimiento oculto en grandes cantidades de datos, recopilados por expertos en diferentes dominios. Por otra parte, las técnicas de visualización también se han usado para mejorar y facilitar este proceso. Sin embargo, existen limitaciones serias en la obtención de conocimiento, ya que suele ser un proceso lento, tedioso y en muchas ocasiones infructífero, debido a la dificultad de las personas para comprender conjuntos de datos de grandes dimensiones. Otro gran inconveniente, pocas veces tenido en cuenta por los expertos que analizan grandes conjuntos de datos, es la degradación involuntaria a la que someten a los datos durante las tareas de análisis, previas a la obtención final de conclusiones. Por degradación quiere decirse que los datos pueden perder sus propiedades originales, y suele producirse por una reducción inapropiada de los datos, alterando así su naturaleza original y llevando en muchos casos a interpretaciones y conclusiones erróneas que podrían tener serias implicaciones. Además, este hecho adquiere una importancia trascendental cuando los datos pertenecen al dominio médico o biológico, y la vida de diferentes personas depende de esta toma final de decisiones, en algunas ocasiones llevada a cabo de forma inapropiada. Ésta es la motivación de la presente tesis, la cual propone un nuevo framework visual, llamado MedVir, que combina la potencia de técnicas avanzadas de visualización y minería de datos para tratar de dar solución a estos grandes inconvenientes existentes en el proceso de descubrimiento de información válida. El objetivo principal es hacer más fácil, comprensible, intuitivo y rápido el proceso de adquisición de conocimiento al que se enfrentan los expertos cuando trabajan con grandes conjuntos de datos en diferentes dominios. Para ello, en primer lugar, se lleva a cabo una fuerte disminución en el tamaño de los datos con el objetivo de facilitar al experto su manejo, y a la vez preservando intactas, en la medida de lo posible, sus propiedades originales. Después, se hace uso de efectivas técnicas de visualización para representar los datos obtenidos, permitiendo al experto interactuar de forma sencilla e intuitiva con los datos, llevar a cabo diferentes tareas de análisis de datos y así estimular visualmente su capacidad de comprensión. De este modo, el objetivo subyacente se basa en abstraer al experto, en la medida de lo posible, de la complejidad de sus datos originales para presentarle una versión más comprensible, que facilite y acelere la tarea final de descubrimiento de conocimiento. MedVir se ha aplicado satisfactoriamente, entre otros, al campo de la magnetoencefalografía (MEG), que consiste en la predicción en la rehabilitación de lesiones cerebrales traumáticas (Traumatic Brain Injury (TBI) rehabilitation prediction). Los resultados obtenidos demuestran la efectividad del framework a la hora de acelerar y facilitar el proceso de descubrimiento de conocimiento sobre conjuntos de datos reales. ABSTRACT Traditionally, the use of data analysis techniques has been one of the main ways of discovering knowledge hidden in large amounts of data, collected by experts in different domains. Moreover, visualization techniques have also been used to enhance and facilitate this process. However, there are serious limitations in the process of knowledge acquisition, as it is often a slow, tedious and many times fruitless process, due to the difficulty for human beings to understand large datasets. Another major drawback, rarely considered by experts that analyze large datasets, is the involuntary degradation to which they subject the data during analysis tasks, prior to obtaining the final conclusions. Degradation means that data can lose part of their original properties, and it is usually caused by improper data reduction, thereby altering their original nature and often leading to erroneous interpretations and conclusions that could have serious implications. Furthermore, this fact gains a trascendental importance when the data belong to medical or biological domain, and the lives of people depends on the final decision-making, which is sometimes conducted improperly. This is the motivation of this thesis, which proposes a new visual framework, called MedVir, which combines the power of advanced visualization techniques and data mining to try to solve these major problems existing in the process of discovery of valid information. Thus, the main objective is to facilitate and to make more understandable, intuitive and fast the process of knowledge acquisition that experts face when working with large datasets in different domains. To achieve this, first, a strong reduction in the size of the data is carried out in order to make the management of the data easier to the expert, while preserving intact, as far as possible, the original properties of the data. Then, effective visualization techniques are used to represent the obtained data, allowing the expert to interact easily and intuitively with the data, to carry out different data analysis tasks, and so visually stimulating their comprehension capacity. Therefore, the underlying objective is based on abstracting the expert, as far as possible, from the complexity of the original data to present him a more understandable version, thus facilitating and accelerating the task of knowledge discovery. MedVir has been succesfully applied to, among others, the field of magnetoencephalography (MEG), which consists in predicting the rehabilitation of Traumatic Brain Injury (TBI). The results obtained successfully demonstrate the effectiveness of the framework to accelerate and facilitate the process of knowledge discovery on real world datasets.

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Situado en el límite entre Ingeniería, Informática y Biología, la mecánica computacional de las neuronas aparece como un nuevo campo interdisciplinar que potencialmente puede ser capaz de abordar problemas clínicos desde una perspectiva diferente. Este campo es multiescala por naturaleza, yendo desde la nanoescala (como, por ejemplo, los dímeros de tubulina) a la macroescala (como, por ejemplo, el tejido cerebral), y tiene como objetivo abordar problemas que son complejos, y algunas veces imposibles, de estudiar con medios experimentales. La modelización computacional ha sido ampliamente empleada en aplicaciones Neurocientíficas tan diversas como el crecimiento neuronal o la propagación de los potenciales de acción compuestos. Sin embargo, en la mayoría de los enfoques de modelización hechos hasta ahora, la interacción entre la célula y el medio/estímulo que la rodea ha sido muy poco explorada. A pesar de la tremenda importancia de esa relación en algunos desafíos médicos—como, por ejemplo, lesiones traumáticas en el cerebro, cáncer, la enfermedad del Alzheimer—un puente que relacione las propiedades electrofisiológicas-químicas y mecánicas desde la escala molecular al nivel celular todavía no existe. Con ese objetivo, esta investigación propone un marco computacional multiescala particularizado para dos escenarios respresentativos: el crecimiento del axón y el acomplamiento electrofisiológicomecánico de las neuritas. En el primer caso, se explora la relación entre los constituyentes moleculares del axón durante su crecimiento y sus propiedades mecánicas resultantes, mientras que en el último, un estímulo mecánico provoca deficiencias funcionales a nivel celular como consecuencia de sus alteraciones electrofisiológicas-químicas. La modelización computacional empleada en este trabajo es el método de las diferencias finitas, y es implementada en un nuevo programa llamado Neurite. Aunque el método de los elementos finitos es también explorado en parte de esta investigación, el método de las diferencias finitas tiene la flexibilidad y versatilidad necesaria para implementar mode los biológicos, así como la simplicidad matemática para extenderlos a simulaciones a gran escala con un coste computacional bajo. Centrándose primero en el efecto de las propiedades electrofisiológicas-químicas sobre las propiedades mecánicas, una versión adaptada de Neurite es desarrollada para simular la polimerización de los microtúbulos en el crecimiento del axón y proporcionar las propiedades mecánicas como función de la ocupación de los microtúbulos. Después de calibrar el modelo de crecimiento del axón frente a resultados experimentales disponibles en la literatura, las características mecánicas pueden ser evaluadas durante la simulación. Las propiedades mecánicas del axón muestran variaciones dramáticas en la punta de éste, donde el cono de crecimiento soporta las señales químicas y mecánicas. Bansándose en el conocimiento ganado con el modelo de diferencias finitas, y con el objetivo de ir de 1D a 3D, este esquema preliminar pero de una naturaleza innovadora allana el camino a futuros estudios con el método de los elementos finitos. Centrándose finalmente en el efecto de las propiedades mecánicas sobre las propiedades electrofisiológicas- químicas, Neurite es empleado para relacionar las cargas mecánicas macroscópicas con las deformaciones y velocidades de deformación a escala microscópica, y simular la propagación de la señal eléctrica en las neuritas bajo carga mecánica. Las simulaciones fueron calibradas con resultados experimentales publicados en la literatura, proporcionando, por tanto, un modelo capaz de predecir las alteraciones de las funciones electrofisiológicas neuronales bajo cargas externas dañinas, y uniendo lesiones mecánicas con las correspondientes deficiencias funcionales. Para abordar simulaciones a gran escala, aunque otras arquitecturas avanzadas basadas en muchos núcleos integrados (MICs) fueron consideradas, los solvers explícito e implícito se implementaron en unidades de procesamiento central (CPU) y unidades de procesamiento gráfico (GPUs). Estudios de escalabilidad fueron llevados acabo para ambas implementaciones mostrando resultados prometedores para casos de simulaciones extremadamente grandes con GPUs. Esta tesis abre la vía para futuros modelos mecánicos con el objetivo de unir las propiedades electrofisiológicas-químicas con las propiedades mecánicas. El objetivo general es mejorar el conocimiento de las comunidades médicas y de bioingeniería sobre la mecánica de las neuronas y las deficiencias funcionales que aparecen de los daños producidos por traumatismos mecánicos, como lesiones traumáticas en el cerebro, o enfermedades neurodegenerativas como la enfermedad del Alzheimer. ABSTRACT Sitting at the interface between Engineering, Computer Science and Biology, Computational Neuron Mechanics appears as a new interdisciplinary field potentially able to tackle clinical problems from a new perspective. This field is multiscale by nature, ranging from the nanoscale (e.g., tubulin dimers) to the macroscale (e.g., brain tissue), and aims at tackling problems that are complex, and sometime impossible, to study through experimental means. Computational modeling has been widely used in different Neuroscience applications as diverse as neuronal growth or compound action potential propagation. However, in the majority of the modeling approaches done in this field to date, the interactions between the cell and its surrounding media/stimulus have been rarely explored. Despite of the tremendous importance of such relationship in several medical challenges—e.g., traumatic brain injury (TBI), cancer, Alzheimer’s disease (AD)—a bridge between electrophysiological-chemical and mechanical properties of neurons from the molecular scale to the cell level is still lacking. To this end, this research proposes a multiscale computational framework particularized for two representative scenarios: axon growth and electrophysiological-mechanical coupling of neurites. In the former case, the relation between the molecular constituents of the axon during its growth and its resulting mechanical properties is explored, whereas in the latter, a mechanical stimulus provokes functional deficits at cell level as a consequence of its electrophysiological-chemical alterations. The computational modeling approach chosen in this work is the finite difference method (FDM), and was implemented in a new program called Neurite. Although the finite element method (FEM) is also explored as part of this research, the FDM provides the necessary flexibility and versatility to implement biological models, as well as the mathematical simplicity to extend them to large scale simulations with a low computational cost. Focusing first on the effect of electrophysiological-chemical properties on the mechanical proper ties, an adaptation of Neurite was developed to simulate microtubule polymerization in axonal growth and provide the axon mechanical properties as a function of microtubule occupancy. After calibrating the axon growth model against experimental results available in the literature, the mechanical characteristics can be tracked during the simulation. The axon mechanical properties show dramatic variations at the tip of the axon, where the growth cone supports the chemical and mechanical signaling. Based on the knowledge gained from the FDM scheme, and in order to go from 1D to 3D, this preliminary yet novel scheme paves the road for future studies with FEM. Focusing then on the effect of mechanical properties on the electrophysiological-chemical properties, Neurite was used to relate macroscopic mechanical loading to microscopic strains and strain rates, and simulate the electrical signal propagation along neurites under mechanical loading. The simulations were calibrated against experimental results published in the literature, thus providing a model able to predict the alteration of neuronal electrophysiological function under external damaging load, and linking mechanical injuries to subsequent acute functional deficits. To undertake large scale simulations, although other state-of-the-art architectures based on many integrated cores (MICs) were considered, the explicit and implicit solvers were implemented for central processing units (CPUs) and graphics processing units (GPUs). Scalability studies were done for both implementations showing promising results for extremely large scale simulations with GPUs. This thesis opens the avenue for future mechanical modeling approaches aimed at linking electrophysiological- chemical properties to mechanical properties. Its overarching goal is to enhance the bioengineering and medical communities knowledge on neuronal mechanics and functional deficits arising from damages produced by direct mechanical insults, such as TBI, or neurodegenerative evolving illness, such as AD.

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With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, function of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells has only very recently been proposed (Jerusalem et al., 2013). In this paper, we present the implementation details of Neurite: the finite difference parallel program used in this reference. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite-explicit and implicit-were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between lectrophysiology and mechanics (Jerusalem et al., 2013). This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented dendritic tree, and a damaged axon. The capabilities of the program to deal with large scale scenarios, segmented neuronal structures, and functional deficits under mechanical loading are specifically highlighted.

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Poly(ADP-ribose) polymerase (PARP) knockout mice are resistant to murine models of human diseases such as cerebral and myocardial ischemia, traumatic brain injury, diabetes, Parkinsonism, endotoxic shock and arthritis, implicating PARP in the pathogenesis of these diseases. Potent selective PARP inhibitors are therefore being evaluated as novel therapeutic agents in the treatment of these diseases. Inhibition or depletion of PARP, however, increases genomic instability in cells exposed to genotoxic agents. We recently demonstrated the presence of a genomically unstable tetraploid population in PARP–/– fibroblasts and its loss after stable transfection with PARP cDNA. To elucidate whether the genomic instability is attributable to PARP deficiency or lack of PARP activity, we investigated the effects of PARP inhibition on development of tetraploidy. Immortalized wild-type and PARP–/– fibroblasts were exposed for 3 weeks to 20 µM GPI 6150 (1,11b-dihydro-[2H]benzopyrano[4,3,2-de]isoquinolin-3-one), a novel small molecule specific competitive inhibitor of PARP (Ki = 60 nM) and one of the most potent PARP inhibitors to date (IC50 = 0.15 µM). Although GPI 6150 initially decreased cell growth in wild-type cells, there was no effect on cell growth or viability after 24 h. GPI 6150 inhibited endogenous PARP activity in wild-type cells by ∼91%, to about the residual levels in PARP–/– cells. Flow cytometric analysis of unsynchronized wild-type cells exposed for 3 weeks to GPI 6150 did not induce the development of tetraploidy, suggesting that, aside from its catalytic function, PARP may play other essential roles in the maintenance of genomic stability.

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The Internet has created new opportunities for librarians to develop information systems that are readily accessible at the point of care. This paper describes the multiyear process used to justify, fund, design, develop, promote, and evaluate a rehabilitation prototype of a point-of-care, team-based information system (PoinTIS) and train health care providers to use this prototype for their spinal cord injury and traumatic brain injury patient care and education activities. PoinTIS is a successful model for librarians in the twenty-first century to serve as publishers of information created or used by their parent organizations and to respond to the opportunities for information dissemination provided by recent technological advances.

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Objetivos: Avaliar a capacidade funcional de pacientes vítimas de trauma um ano após alta hospitalar e verificar associação da capacidade funcional com fatores relacionados ao trauma e à internação hospitalar. Metodologia: Estudo de coorte prospectivo, com pacientes vítimas de trauma grave (Injury Severity Score - ISS >=16), internados entre Junho e Setembro de 2010 em unidade de terapia intensiva (UTI) cirúrgica especializada em paciente politraumatizado de um hospital público de grande porte na cidade de São Paulo, Brasil. Variáveis de interesse como idade, sexo, escore de Glasgow, Acute Physiology and Chronic Health Disease Classification System II (APACHE II), mecanismos de trauma, número de lesões, região corpórea afetada, número de cirurgias, duração da ventilação mecânica (VM) e tempo de internação hospitalar foram coletadas dos prontuários médicos. A capacidade funcional foi avaliada um ano após alta hospitalar utilizando as escalas Glasgow Outcome Scale (GOS) e Escala de Atividades Instrumentais de Vida Diária de Lawton (AIVDL). Os pacientes também foram questionados se haviam retornado ao trabalho ou estudo. Resultados: O seguimento um ano após trauma foi completo em 49 indivíduos, a maioria composta por jovens (36±11 anos), do sexo masculino (81,6%) e vítimas de acidentes de trânsito (71,5%). Cada indivíduo sofreu aproximadamente 4 lesões corporais, acarretando uma média no ISS de 31 ± 14,4. O traumatismo cranioencefálico foi o tipo de lesão mais comum (65,3%). De acordo com a GOS, a maioria dos pacientes apresentou disfunção moderada (43%) ou disfunção leve ou ausente (37%) um ano após o trauma. A escala AIVDL apresentou pontuação média de 12±4 com aproximadamente 60- 70% dos indivíduos capazes de realizar de forma independente a maioria das atividades avaliadas. Escore de Glasgow, APACHE II, duração da VM e tempo de internação hospitalar foram associadas com a capacidade funcional um ano após lesão. A regressão linear múltipla considerando todas as variáveis significativas revelou associação entre a pontuação da escala AIVDL e o tempo de internação hospitalar. Apenas 32,6% dos indivíduos retornaram ao trabalho ou estudo. Conclusões: A maioria dos pacientes vítimas de trauma grave foi capaz de realizar as atividades avaliadas com independência; apenas um terço deles retornou ao trabalho e/ou estudo um ano após alta hospitalar. O tempo de internação hospitalar foi revelado como preditor significativo para a recuperação da capacidade funcional um ano após lesão grave

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The utilization of symptom validity tests (SVTs) in pediatric assessment is receiving increasing empirical support. The Rey 15-Item Test (FIT) is an SVT commonly used in adult assessment, with limited research in pediatric populations. Given that FIT classification statistics across studies to date have been quite variable, Boone, Salazar, Lu, Warner-Chacon, and Razani (2002) developed a recognition trial to use with the original measure to enhance accuracy. The current study aims to assess the utility of the FIT and recognition trial in a pediatric mild traumatic brain injury (TBI) sample (N = 112; M = 14.6 years), in which a suboptimal effort base rate of 17% has been previously established (Kirkwood & Kirk, 2010). All participants were administered the FIT as part of an abbreviated neuropsychological evaluation; failure on the Medical Symptom Validity Test (MSVT) was used as the criterion for suspect effort. The traditional adult cut-off score of(99%), but poor sensitivity (6%). When the recognition trial was also utilized, a combination score of(sensitivity = 64%, specificity = 93%). Results indicate that the FIT with recognition trial may be useful in the assessment of pediatric suboptimal effort, at least among relatively high functioning children following mild TBI.

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Concussive injuries appear to be becoming a more common occurrence among athletes. While many studies have assessed the short-term and long-term effects of concussive injuries, fewer studies have specifically addressed the impact of multiple concussive injuries within a high school population. Through the use of the Immediate Post-Concussion Assessment and Cognitive Testing measure (ImPACT), this study investigated differences in a sample of 946 high school athletes with varying concussive histories (multiple concussions vs. single concussion vs. no concussion) at baseline and following sustaining a concussive injury. An additional analysis was conducted with athletes who obtained two concussions within the study to assess for trends in symptomology between their first and second injuries. For both baseline and study concussed athletes, athletes with multiple concussive injuries did not exhibit significantly elevated self-report symptoms nor decreased ImPACT composite scores compared to the other groups. Analysis of data from athletes who sustained more than one concussion within the study, revealed an increase in self-report symptoms and a decrease in ImPACT performance from time 1 to time 2. However, these changes were small in magnitude and were not consistently exhibited across the variables under investigation. Overall, this study did not find compelling evidence of increased symptomological patterns or decreased functioning for multiple concussed athletes as compared to peers.

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Although initially conceived as providing simply the preventive portion of an extended continuum of care for veterans, the Driving Under the Influence (DUI) program has turned out to be an important outreach service for active duty or recently discharged OEF/OIF (Operation Enduring Freedom/Operation Iraqi Freedom) veterans. Veterans receive empirically-based, state-mandated education and therapy under the only Department of Veterans Affairs (VA) - sponsored DUI program in the State of Colorado, with the advantage of having providers who are sensitive to symptoms of Post-Traumatic Stress Disorder (PTSD) and other relevant diagnoses specific to this population, including Traumatic Brain Injury (TBI). In this paper, the rapid growth of this program is described, as well as summary data regarding the completion, discontinuation, and augmentation of services from the original referral concern. Key results indicated that for nearly one third (31.9%) of the OEF/OIF veterans who were enrolled in the DUI program, this was their initial contact with the VA health care system. Furthermore, following their enrollment in the DUI program, more than one fourth (27.6%) were later referred to and attended other VA programs including PTSD rehabilitation and group therapy, anger management, and intensive inpatient or outpatient dual diagnosis programs. These and other findings from this study suggest that the DUI program may be an effective additional pathway for providing treatment that is particularly salient to the distinctive OEF/OIF population; one that may also result in earlier intervention for problem drinking and other problems related to combat. Relevant conclusions discussed herein primarily aim to improve providers' understanding of effective outreach, and to enhance the appropriate linkages between OEF/OIF veterans and existing VA services.

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Introduction et recension des écrits : Récemment, les suicides de vétérans et d’athlètes professionnels ont attiré l’attention sur l’association entre le TCC et le suicide. Les lignes directrices concernant la prise en charge en santé mentale dans cette population demeurent fragmentaires. Les objectifs de cette thèse sont de 1) déterminer si une association existe entre le TCC subi dans l’enfance et le suicide futur, 2) explorer si les personnes qui se sont suicidées ont consulté un psychiatre dans l’année précédant le suicide et évaluer si cela diffère selon que la personne ait eu un TCC ou non, 3) décrire et qualifier l’offre québécoise de santé mentale offerte en réadaptation aux enfants et aux adultes ayant subi un TCC. Méthodologie : Le volet épidémiologique consiste en une étude de cohorte rétrospective sur un échantillon de 135 703 enfants ayant reçu des services médicaux au Québec en 1987 et suivis jusqu’en 2008. Le volet qualitatif comprend un sondage auprès des gestionnaires des programmes de réadaptation TCC du Québec, des groupes de discussion avec des cliniciens et des entrevues avec des survivants de TCC et leurs proches. Résultats : Notre étude épidémiologique confirme une association significative entre le TCC subi dans l’enfance (HR 1,49 IC95% 1,04- 2,14), dans l’adolescence (HR 1,57, IC 95% 1,09-2,26) et à l’âge adulte (HR 2,53, IC95% 1,79-3,59) et le suicide. Malgré un risque de suicide plus élevé, les personnes avec un TCC et qui se sont suicidées n’ont pas consulté de psychiatre plus fréquemment que les personnes sans TCC (OR 1,29, IC 95% 0,75- 2,24). Par ailleurs, notre étude qualitative révèle que les forces du système actuel incluent une bonne qualité des services, mais qu’il existe des faiblesses au niveau de l’accès aux médecins spécialisés, du dépistage systématique et de l’accès aux services à long terme. Nos recommandations incluent le développement d’une approche coordonnée en santé mentale, l’implication automatique d’un gestionnaire de cas et l’amélioration des mécanismes d’accès après le congé.