994 resultados para AK22-1941


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BACKGROUND Several studies in recent years have evaluated Health Related Quality of Life (HRQoL) of patients with primary hyperparathyroidism (PHPT). No disease specific questionnaires are available to assess the impact of the disease. The aim of this research is to describe the development of a new disease specific Quality of Life (QoL) questionnaire for use specifically with PHPT patients. METHODS A conceptual model was developed describing the impact of the disease and its symptoms on QoL domains. A literature review was conducted to identify the most relevant domains. A focus group with experts was used to validate the domains; 24 patients were also interviewed to complement the information from the patient's perspective. A content analysis of the interviews was performed to identify items related with the impact of the disease, leading to PHPQoL-V.1 which was presented to a sample of 67 patients. Reliability was assessed by Cronbach's coefficient alpha and item-total score correlations. Validity was assessed by a factor analysis performed to determine the number of domains. Rasch analysis was carried out in order to refine the questionnaire items. RESULTS 259 items were extracted from the interviews that were subsequently reduced to 34 items. Cronbach's coefficient alpha was 0.92. The factor analysis extracted two domains (physical and emotional). After Rasch analysis the questionnaire PHPQoL-V.2 kept 16 items (9 physical and 7 emotional). The questionnaire was developed in a Spanish population and the final version was translated to English through translation and back-translation. CONCLUSION The first disease specific HRQoL questionnaire for PHPT patients (PHPQoL-16) has been developed. Validation studies designed to assess measurement properties of this tool are currently underway.

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We propose a segmentation method based on the geometric representation of images as 2-D manifolds embedded in a higher dimensional space. The segmentation is formulated as a minimization problem, where the contours are described by a level set function and the objective functional corresponds to the surface of the image manifold. In this geometric framework, both data-fidelity and regularity terms of the segmentation are represented by a single functional that intrinsically aligns the gradients of the level set function with the gradients of the image and results in a segmentation criterion that exploits the directional information of image gradients to overcome image inhomogeneities and fragmented contours. The proposed formulation combines this robust alignment of gradients with attractive properties of previous methods developed in the same geometric framework: 1) the natural coupling of image channels proposed for anisotropic diffusion and 2) the ability of subjective surfaces to detect weak edges and close fragmented boundaries. The potential of such a geometric approach lies in the general definition of Riemannian manifolds, which naturally generalizes existing segmentation methods (the geodesic active contours, the active contours without edges, and the robust edge integrator) to higher dimensional spaces, non-flat images, and feature spaces. Our experiments show that the proposed technique improves the segmentation of multi-channel images, images subject to inhomogeneities, and images characterized by geometric structures like ridges or valleys.

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In this review, we discuss genetic evidence supporting Guyton's hypothesis stating that blood pressure control is critically depending on fluid handling by the kidney. The review is focused on the genetic dissection of sodium and potassium transport in the distal nephron and the collecting duct that are the most important sites for the control of sodium and potassium balance by aldosterone and angiotensin II. Thanks to the study of Mendelian forms of hypertension and their corresponding transgenic mouse models, three main classes of diuretic receptors (furosemide, thiazide, amiloride) and the main components of the aldosterone- and angiotensin-dependent signaling pathways were molecularly identified over the past 20years. This will allow to design rational strategies for the treatment of hypertension and for the development of the next generation of diuretics.