4 resultados para Chest

em Universidad Politécnica de Madrid


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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.

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Thermography for scientific research and practical purposes requires a series of procedures to obtain images that should be standardized; one of the most important is the time required for acclimatization in the controlled environment. Thus, the objective of this study was to identify the appropriate acclimatization time in rest to reach a thermal balance on young people skin. Forty-four subjects participated in the study, 18 men (22.3 ± 3.1 years) and 26 women (21.7 ± 2.5 years). Thermographic images were collected using a thermal imager (Fluke ®), totaling 44 images over a period of 20 minutes. The skin temperature (TSK) was measured at the point of examination which included the 0 minute, 2, 4, 6, 8, 10, 12, 14, 16, 18 and 20. The body regions of interest (ROI) analyzed included the hands, forearms, arms, thighs, legs, chest and abdomen. We used the Friedman test with post hoc Dunn?s in order to establish the time at rest required to obtain a TSK balance and the Mann-Whitney test was used to compare age, BMI, body fat percentage and temperature variations between men and women, considering always a significance level of pmenor que0.05. Results showed that women had significantly higher temperature variations than men (pmenor que0.01) along the time. In men, only the body region of the abdomen obtained a significant variance (pmenor que0.05) on the analyzed period, both in the anterior and posterior part. In women, the anterior abdomen and thighs, and the posterior part of the hands, forearms and abdomen showed significant differences (pmenor que0.05). Based on our results, it can be concluded that the time in rest condition required reaching a TSK balance in young men and women is variable, but for whole body analysis it is recommended at least 10 minutes for both sexes.

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Se comenzó el trabajo recabando información sobre los distintos enfoques que se le había dado a la anotación a lo largo del tiempo, desde anotación de imágenes a mano, pasando por anotación de imágenes utilizando características de bajo nivel, como color y textura, hasta la anotación automática. Tras entrar en materia, se procedió a estudiar artículos relativos a los diferentes algoritmos utilizados para la anotación automática de imágenes. Dado que la anotación automática es un campo bastante abierto, hay un gran numero de enfoques. Teniendo las características de las imágenes en particular en las que se iba a centrar el proyecto, se fueron descartando los poco idoneos, bien por un coste computacional elevado, o porque estaba centrado en un tipo diferente de imágenes, entre otras cosas. Finalmente, se encontró un algoritmo basado en formas (Active Shape Model) que se consideró que podría funcionar adecuadamente. Básicamente, los diferentes objetos de la imagen son identicados a partir de un contorno base generado a partir de imágenes de muestra, siendo modicado automáticamente para cubrir la zona deseada. Dado que las imágenes usadas son todas muy similares en composición, se cree que puede funcionar bien. Se partió de una implementación del algoritmo programada en MATLAB. Para empezar, se obtuvieron una serie de radiografías del tórax ya anotadas. Las imágenes contenían datos de contorno para ambos pulmones, las dos clavículas y el corazón. El primer paso fue la creación de una serie de scripts en MATLAB que permitieran: - Leer y transformar las imágenes recibidas en RAW, para adaptarlas al tamaño y la posición de los contornos anotados - Leer los archivos de texto con los datos de los puntos del contorno y transformarlos en variables de MATLAB - Unir la imagen transformada con los puntos y guardarla en un formato que la implementación del algoritmo entendiera. Tras conseguir los ficheros necesarios, se procedió a crear un modelo para cada órgano utilizando para el entrenamiento una pequeña parte de las imágenes. El modelo obtenido se probó con varias imágenes de las restantes. Sin embargo, se encontro bastante variación dependiendo de la imagen utilizada y el órgano detectado. ---ABSTRACT---The project was started by procuring information about the diferent approaches to image annotation over time, from manual image anotation to automatic annotation. The next step was to study several articles about the diferent algorithms used for automatic image annotation. Given that automatic annotation is an open field, there is a great number of approaches. Taking into account the features of the images that would be used, the less suitable algorithms were rejected. Eventually, a shape-based algorithm (Active Shape Model) was found. Basically, the diferent objects in the image are identified from a base contour, which is generated from training images. Then this contour is automatically modified to cover the desired area. Given that all the images that would be used are similar in object placement, the algorithm would probably work nicely. The work started from a MATLAB implementation of the algorithm. To begin with, a set of chest radiographs already annotated were obtained. These images came with contour data for both lungs, both clavicles and the heart. The first step was the creation of a series of MATLAB scripts to join the RAW images with the annotation data and transform them into a format that the algorithm could read. After obtaining the necessary files, a model for each organ was created using part of the images for training. The trained model was tested on several of the reimaining images. However, there was much variation in the results from one image to another. Generally, lungs were detected pretty accurately, whereas clavicles and the heart gave more problems. To improve the method, a new model was trained using half of the available images. With this model, a significant inprovement of the results can be seen.

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Bakers are repeatedly exposed to wheat flour (WF) and may develop sensitization and occupational rhinoconjunctivitis and/or asthma to WF allergens.1 Several wheat proteins have been identified as causative allergens of occupational respiratory allergy in bakery workers.1 Testing of IgE reactivity in patients with different clinical profiles of wheat allergy (food allergy, wheat-dependent exercise-induced anaphylaxis, and baker's asthma) to salt-soluble and salt-insoluble protein fractions from WF revealed a high degree of heterogeneity in the recognized allergens. However, mainly salt-soluble proteins (albumins, globulins) seem to be associated with baker's asthma, and prolamins (gliadins, glutenins) with wheat-dependent exercise-induced anaphylaxis, whereas both protein fractions reacted to IgE from food-allergic patients.1 Notwithstanding, gliadins have also been incriminated as causative allergens in baker's asthma.2 We report on a 31-year-old woman who had been exposed to WF practically since birth because her family owned a bakery housed in the same home where they lived. She moved from this house when she was 25 years, but she continued working every day in the family bakery. In the last 8 years she had suffered from work-related nasal and ocular symptoms such as itching, watery eyes, sneezing, nasal stuffiness, and rhinorrhea. These symptoms markedly improved when away from work and worsened at work. In the last 5 years, she had also experienced dysphagia with frequent choking, especially when ingesting meats or cephalopods, which had partially improved with omeprazole therapy. Two years before referral to our clinic, she began to have dry cough and breathlessness, which she also attributed to her work environment. Upper and lower respiratory tract symptoms increased when sifting the WF and making the dough. The patient did not experience gastrointestinal symptoms with ingestion of cereal products. Skin prick test results were positive to grass (mean wheal, 6 mm), cypress (5 mm) and Russian thistle pollen (4 mm), WF (4 mm), and peach lipid transfer protein (6 mm) and were negative to rice flour, corn flour, profilin, mites, molds, and animal dander. Skin prick test with a homemade WF extract (10% wt/vol) was strongly positive (15 mm). Serologic tests yielded the following results: eosinophil cationic protein, 47 ?g/L; total serum IgE, 74 kU/L; specific IgE (ImmunoCAP; ThermoFisher, Uppsala, Sweden) to WF, 7.4 kU/L; barley flour, 1.24 kU/L; and corn, gluten, alpha-amylase, peach, and apple, less than 0.35 kU/L. Specific IgE binding to microarrayed purified WF allergens (WDAI-0.19, WDAI-0.53, WTAI-CM1, WTAI-CM2, WTAI-CM3, WTAI-CM16, WTAI-CM17, Tri a 14, profilin, ?-5-gliadin, Tri a Bd 36 and Tri a TLP, and gliadin and glutamine fractions) was assessed as described elsewhere.3 The patient's serum specifically recognized ?-5-gliadin and the gliadin fraction, and no IgE reactivity was observed to other wheat allergens. Spirometry revealed a forced vital capacity of 3.88 L (88%), an FEV1 of 3.04 L (87%), and FEV1/forced vital capacity of 83%. A methacholine inhalation test was performed following an abbreviated protocol,4 and the results were expressed as PD20 in cumulative dose (mg) of methacholine. Methacholine inhalation challenge test result was positive (0.24 mg cumulative dose) when she was working, and after a 3-month period away from work and with no visits to the bakery house, it gave a negative result. A chest x-ray was normal. Specific inhalation challenge test was carried out in the hospital laboratory by tipping WF from one tray to another for 15 minutes. Spirometry was performed at baseline and at 2, 5, 10, 15, 20, 30, 45, and 60 minutes after the challenge with WF. Peak expiratory flow was measured at baseline and then hourly over 24 hours (respecting sleeping time). A 12% fall in FEV1 was observed at 20 minutes and a 26% drop in peak expiratory flow at 9 hours after exposure to WF,