Epidemiological characteristics and diagnostic approach in patients admitted to the emergency room for transient loos of consciousness: Group for Syncope Study in the Emergency Room (GESINUR) study

Aims: To assess the clinical presentation and acute management of patients with transient loss of consciousness (T-LOC) in the emergency department (ED). Methods and results: A multi-centre prospective observational study was carried out in 19 Spanish hospitals over 1 month. The patients included were 14 years old and were admitted to the ED because of an episode of T-LOC. Questionnaires and corresponding electrocardiograms (ECGs) were reviewed by a Steering Committee (SC) to unify diagnostic criteria, evaluate adherence to guidelines, and diagnose correctly the ECGs. We included 1419 patients (prevalence, 1.14%).ECG was performed in 1335 patients (94%) in the ED: 498 (37.3%) ECGs were classified as abnormal. The positive diagnostic yield ranged from 0% for the chest X-ray to 12% for the orthostatic test. In the ED, 1217 (86%) patients received a final diagnosis of syncope, whereas the remaining 202 (14%) were diagnosed of non-syncopal transient lossof consciousness (NST-LOC). After final review by the SC, 1080 patients (76%) were diagnosed of syncope, whereas 339 (24%) were diagnosed of NST-LOC (P , 0.001). Syncope was diagnosed correctly in 84% of patients. Only 25% of patients with T-LOC were admitted to hospitals. Conclusion Adherence to clinical guidelines for syncope management was low; many diagnostic tests were performed with low diagnostic yield. Important differences were observed between syncope diagnoses at the ED and by SC decision.

Design and integration of lower ports for ITER diagnostic systems

All around the ITER vacuum vessel, forty-four ports will provide access to the vacuum vessel for remotehandling operations, diagnostic systems, heating, and vacuum systems: 18 upper ports, 17 equatorialports, and 9 lower ports. Among the lower ports, three of them will be used for the remote handlinginstallation of the ITER divertor. Once the divertor is in place, these ports will host various diagnosticsystems mounted in the so-called diagnostic racks. The diagnostic racks must allow the support andcooling of the diagnostics, extraction of the required diagnostic signals, and providing access and main-tainability while minimizing the leakage of radiation toward the back of the port where the humans areallowed to enter. A fully integrated inner rack, carrying the near plasma diagnostic components, will bean stainless steel structure, 4.2 m long, with a maximum weight of 10 t. This structure brings water forcooling and baking at maximum temperature of 240?C and provides connection with gas, vacuum andelectric services. Additional racks (placed away from plasma and not requiring cooling) may be requiredfor the support of some particular diagnostic components. The diagnostics racks and its associated exvessel structures, which are in its conceptual design phase, are being designed to survive the lifetimeof ITER of 20 years. This paper presents the current state of development including interfaces, diagnos-tic integration, operation and maintenance, shielding requirements, remote handling, loads cases anddiscussion of the main challenges coming from the severe environment and engineering requirements.

Mechanical behaviour and rupture of normal and pathological human ascending aortic wall

The mechanical properties of aortic wall, both healthy and pathological, are needed in order to develop and improve diagnostic and interventional criteria, and for the development of mechanical models to assess arterial integrity. This study focuses on the mechanical behaviour and rupture conditions of the human ascending aorta and its relationship with age and pathologies. Fresh ascending aortic specimens harvested from 23 healthy donors, 12 patients with bicuspid aortic valve (BAV) and 14 with aneurysm were tensile-tested in vitro under physiological conditions. Tensile strength, stretch at failure and elbow stress were measured. The obtained results showed that age causes a major reduction in the mechanical parameters of healthy ascending aortic tissue, and that no significant differences are found between the mechanical strength of aneurysmal or BAV aortic specimens and the corresponding age-matched control group. The physiological level of the stress in the circumferential direction was also computed to assess the physiological operation range of healthy and diseased ascending aortas. The mean physiological wall stress acting on pathologic aortas was found to be far from rupture, with factors of safety (defined as the ratio of tensile strength to the mean wall stress) larger than six. In contrast, the physiological operation of pathologic vessels lays in the stiff part of the response curve, losing part of its function of damping the pressure waves from the heart.

Deployment and validation of a smart system for screening of language disorders in primary care

Neuro-evolutive development from birth until the age of six years is a decisive factor in a child?s quality of life. Early detection of development disorders in early childhood can facilitate necessary diagnosis and/or treatment. Primary-care pediatricians play a key role in its detection as they can undertake the preventive and therapeutic actions requested to promote a child?s optimal development. However, the lack of time and little specific knowledge at primary-care avoid to applying continuous early-detection anomalies procedures. This research paper focuses on the deployment and evaluation of a smart system that enhances the screening of language disorders in primary care. Pediatricians get support to proceed with early referral of language disorders. The proposed model provides them with a decision-support tool for referral actions to trigger essential diagnostic and/or therapeutic actions for a comprehensive individual development. The research was conducted by starting from a sample of 60 cases of children with language disorders. Validation was carried out through two complementary steps: first, by including a team of seven experts from the fields of neonatology, pediatrics, neurology and language therapy, and, second, through the evaluation of 21 more previously diagnosed cases. The results obtained show that therapist positively accepted the system proposal in 18 cases (86%) and suggested system redesign for single referral to a speech therapist in three remaining cases.

Diagnosis and Management of Grain-Induced Asthma

Grain-induced asthma is a frequent occupational allergic disease mainly caused by inhalation of cereal flour or powder. The main professions affected are bakers, confectioners, pastry factory workers, millers, farmers, and cereal handlers. This disorder is usually due to an IgE-mediated allergic response to inhalation of cereal flour proteins. The major causative allergens of grain-related asthma are proteins derived from wheat, rye and barley flour, although baking additives, such as fungal α-amylase are also important. This review deals with the current diagnosis and treatment of grain-induced asthma, emphasizing the role of cereal allergens as molecular tools to enhance diagnosis and management of this disorder. Asthma-like symptoms caused by endotoxin exposure among grain workers are beyond the scope of this review. Progress is being made in the characterization of grain and bakery allergens, particularly cereal-derived allergens, as well as in the standardization of allergy tests. Salt-soluble proteins (albumins plus globulins), particularly members of the α-amylase/trypsin inhibitor family, thioredoxins, peroxidase, lipid transfer protein and other soluble enzymes show the strongest IgE reactivities in wheat flour. In addition, prolamins (not extractable by salt solutions) have also been claimed as potential allergens. However, the large variability of IgE-binding patterns of cereal proteins among patients with grain-induced asthma, together with the great differences in the concentrations of potential allergens observed in commercial cereal extracts used for diagnosis, highlight the necessity to standardize and improve the diagnostic tools. Removal from exposure to the offending agents is the cornerstone of the management of grain-induced asthma. The availability of purified allergens should be very helpful for a more refined diagnosis, and new immunomodulatory treatments, including allergen immunotherapy and biological drugs, should aid in the management of patients with this disorder.

Automated detection and classification of brain injury lesions on structural magnetic resonance imaging

El daño cerebral adquirido (DCA) es un problema social y sanitario grave, de magnitud creciente y de una gran complejidad diagnóstica y terapéutica. Su elevada incidencia, junto con el aumento de la supervivencia de los pacientes, una vez superada la fase aguda, lo convierten también en un problema de alta prevalencia. En concreto, según la Organización Mundial de la Salud (OMS) el DCA estará entre las 10 causas más comunes de discapacidad en el año 2020. La neurorrehabilitación permite mejorar el déficit tanto cognitivo como funcional y aumentar la autonomía de las personas con DCA. Con la incorporación de nuevas soluciones tecnológicas al proceso de neurorrehabilitación se pretende alcanzar un nuevo paradigma donde se puedan diseñar tratamientos que sean intensivos, personalizados, monitorizados y basados en la evidencia. Ya que son estas cuatro características las que aseguran que los tratamientos son eficaces. A diferencia de la mayor parte de las disciplinas médicas, no existen asociaciones de síntomas y signos de la alteración cognitiva que faciliten la orientación terapéutica. Actualmente, los tratamientos de neurorrehabilitación se diseñan en base a los resultados obtenidos en una batería de evaluación neuropsicológica que evalúa el nivel de afectación de cada una de las funciones cognitivas (memoria, atención, funciones ejecutivas, etc.). La línea de investigación en la que se enmarca este trabajo de investigación pretende diseñar y desarrollar un perfil cognitivo basado no sólo en el resultado obtenido en esa batería de test, sino también en información teórica que engloba tanto estructuras anatómicas como relaciones funcionales e información anatómica obtenida de los estudios de imagen. De esta forma, el perfil cognitivo utilizado para diseñar los tratamientos integra información personalizada y basada en la evidencia. Las técnicas de neuroimagen representan una herramienta fundamental en la identificación de lesiones para la generación de estos perfiles cognitivos. La aproximación clásica utilizada en la identificación de lesiones consiste en delinear manualmente regiones anatómicas cerebrales. Esta aproximación presenta diversos problemas relacionados con inconsistencias de criterio entre distintos clínicos, reproducibilidad y tiempo. Por tanto, la automatización de este procedimiento es fundamental para asegurar una extracción objetiva de información. La delineación automática de regiones anatómicas se realiza mediante el registro tanto contra atlas como contra otros estudios de imagen de distintos sujetos. Sin embargo, los cambios patológicos asociados al DCA están siempre asociados a anormalidades de intensidad y/o cambios en la localización de las estructuras. Este hecho provoca que los algoritmos de registro tradicionales basados en intensidad no funcionen correctamente y requieran la intervención del clínico para seleccionar ciertos puntos (que en esta tesis hemos denominado puntos singulares). Además estos algoritmos tampoco permiten que se produzcan deformaciones grandes deslocalizadas. Hecho que también puede ocurrir ante la presencia de lesiones provocadas por un accidente cerebrovascular (ACV) o un traumatismo craneoencefálico (TCE). Esta tesis se centra en el diseño, desarrollo e implementación de una metodología para la detección automática de estructuras lesionadas que integra algoritmos cuyo objetivo principal es generar resultados que puedan ser reproducibles y objetivos. Esta metodología se divide en cuatro etapas: pre-procesado, identificación de puntos singulares, registro y detección de lesiones. Los trabajos y resultados alcanzados en esta tesis son los siguientes: Pre-procesado. En esta primera etapa el objetivo es homogeneizar todos los datos de entrada con el objetivo de poder extraer conclusiones válidas de los resultados obtenidos. Esta etapa, por tanto, tiene un gran impacto en los resultados finales. Se compone de tres operaciones: eliminación del cráneo, normalización en intensidad y normalización espacial. Identificación de puntos singulares. El objetivo de esta etapa es automatizar la identificación de puntos anatómicos (puntos singulares). Esta etapa equivale a la identificación manual de puntos anatómicos por parte del clínico, permitiendo: identificar un mayor número de puntos lo que se traduce en mayor información; eliminar el factor asociado a la variabilidad inter-sujeto, por tanto, los resultados son reproducibles y objetivos; y elimina el tiempo invertido en el marcado manual de puntos. Este trabajo de investigación propone un algoritmo de identificación de puntos singulares (descriptor) basado en una solución multi-detector y que contiene información multi-paramétrica: espacial y asociada a la intensidad. Este algoritmo ha sido contrastado con otros algoritmos similares encontrados en el estado del arte. Registro. En esta etapa se pretenden poner en concordancia espacial dos estudios de imagen de sujetos/pacientes distintos. El algoritmo propuesto en este trabajo de investigación está basado en descriptores y su principal objetivo es el cálculo de un campo vectorial que permita introducir deformaciones deslocalizadas en la imagen (en distintas regiones de la imagen) y tan grandes como indique el vector de deformación asociado. El algoritmo propuesto ha sido comparado con otros algoritmos de registro utilizados en aplicaciones de neuroimagen que se utilizan con estudios de sujetos control. Los resultados obtenidos son prometedores y representan un nuevo contexto para la identificación automática de estructuras. Identificación de lesiones. En esta última etapa se identifican aquellas estructuras cuyas características asociadas a la localización espacial y al área o volumen han sido modificadas con respecto a una situación de normalidad. Para ello se realiza un estudio estadístico del atlas que se vaya a utilizar y se establecen los parámetros estadísticos de normalidad asociados a la localización y al área. En función de las estructuras delineadas en el atlas, se podrán identificar más o menos estructuras anatómicas, siendo nuestra metodología independiente del atlas seleccionado. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la identificación automática de lesiones utilizando estudios de imagen médica estructural, concretamente estudios de resonancia magnética. Basándose en estos cimientos, se han abrir nuevos campos de investigación que contribuyan a la mejora en la detección de lesiones. ABSTRACT Brain injury constitutes a serious social and health problem of increasing magnitude and of great diagnostic and therapeutic complexity. Its high incidence and survival rate, after the initial critical phases, makes it a prevalent problem that needs to be addressed. In particular, according to the World Health Organization (WHO), brain injury will be among the 10 most common causes of disability by 2020. Neurorehabilitation improves both cognitive and functional deficits and increases the autonomy of brain injury patients. The incorporation of new technologies to the neurorehabilitation tries to reach a new paradigm focused on designing intensive, personalized, monitored and evidence-based treatments. Since these four characteristics ensure the effectivity of treatments. Contrary to most medical disciplines, it is not possible to link symptoms and cognitive disorder syndromes, to assist the therapist. Currently, neurorehabilitation treatments are planned considering the results obtained from a neuropsychological assessment battery, which evaluates the functional impairment of each cognitive function (memory, attention, executive functions, etc.). The research line, on which this PhD falls under, aims to design and develop a cognitive profile based not only on the results obtained in the assessment battery, but also on theoretical information that includes both anatomical structures and functional relationships and anatomical information obtained from medical imaging studies, such as magnetic resonance. Therefore, the cognitive profile used to design these treatments integrates information personalized and evidence-based. Neuroimaging techniques represent an essential tool to identify lesions and generate this type of cognitive dysfunctional profiles. Manual delineation of brain anatomical regions is the classical approach to identify brain anatomical regions. Manual approaches present several problems related to inconsistencies across different clinicians, time and repeatability. Automated delineation is done by registering brains to one another or to a template. However, when imaging studies contain lesions, there are several intensity abnormalities and location alterations that reduce the performance of most of the registration algorithms based on intensity parameters. Thus, specialists may have to manually interact with imaging studies to select landmarks (called singular points in this PhD) or identify regions of interest. These two solutions have the same inconvenient than manual approaches, mentioned before. Moreover, these registration algorithms do not allow large and distributed deformations. This type of deformations may also appear when a stroke or a traumatic brain injury (TBI) occur. This PhD is focused on the design, development and implementation of a new methodology to automatically identify lesions in anatomical structures. This methodology integrates algorithms whose main objective is to generate objective and reproducible results. It is divided into four stages: pre-processing, singular points identification, registration and lesion detection. Pre-processing stage. In this first stage, the aim is to standardize all input data in order to be able to draw valid conclusions from the results. Therefore, this stage has a direct impact on the final results. It consists of three steps: skull-stripping, spatial and intensity normalization. Singular points identification. This stage aims to automatize the identification of anatomical points (singular points). It involves the manual identification of anatomical points by the clinician. This automatic identification allows to identify a greater number of points which results in more information; to remove the factor associated to inter-subject variability and thus, the results are reproducible and objective; and to eliminate the time spent on manual marking. This PhD proposed an algorithm to automatically identify singular points (descriptor) based on a multi-detector approach. This algorithm contains multi-parametric (spatial and intensity) information. This algorithm has been compared with other similar algorithms found on the state of the art. Registration. The goal of this stage is to put in spatial correspondence two imaging studies of different subjects/patients. The algorithm proposed in this PhD is based on descriptors. Its main objective is to compute a vector field to introduce distributed deformations (changes in different imaging regions), as large as the deformation vector indicates. The proposed algorithm has been compared with other registration algorithms used on different neuroimaging applications which are used with control subjects. The obtained results are promising and they represent a new context for the automatic identification of anatomical structures. Lesion identification. This final stage aims to identify those anatomical structures whose characteristics associated to spatial location and area or volume has been modified with respect to a normal state. A statistical study of the atlas to be used is performed to establish which are the statistical parameters associated to the normal state. The anatomical structures that may be identified depend on the selected anatomical structures identified on the atlas. The proposed methodology is independent from the selected atlas. Overall, this PhD corroborates the investigated research hypotheses regarding the automatic identification of lesions based on structural medical imaging studies (resonance magnetic studies). Based on these foundations, new research fields to improve the automatic identification of lesions in brain injury can be proposed.