Patología del primer radio: evaluación por radiodiagnóstico y variables asociadas

[Resumen] Introducción: El primer radio constituye una unidad funcional cuya importancia radica en el papel que desarrolla en las distintas fases de la marcha, siendo también una pieza fundamental a la hora de formar el arco longitudinal interno, capaz de adaptarse a las irregularidades del terreno, así como de volverse una entidad rígida para poder propulsar el pie y el resto del cuerpo hacia adelante. La patología localizada en el primer radio alterará la función del pie directamente, al mismo tiempo que cursará con sintomatología muy diversa. Por ello, es imprescindible conocer bien la anatomía de este segmento y las diferentes alteraciones morfoestructurales que pudieran comprometer la correcta función de la estructura. Objetivos: El objetivo de este estudio es el de analizar mediante imágenes radiográficas distintos parámetros que puedan influir en la correcta función del primer radio, además de relacionar la presencia de diversas alteraciones con el impacto que pudieran tener en la vida cotidiana de los participantes del estudio. Metodología: Se trata de un estudio observacional, transversal de prevalencia realizado con una muestra de 95 pacientes de carácter voluntario. Se desarrollará en la Clínica Universitaria de Podología de la UDC. La recogida de datos consistirá en analizar diferentes tipos de variables, desde variantes antropométricas, pasando por diferencias relativas al funcionamiento y a la movilidad del primer radio y hasta parámetros medibles mediante imágenes radiológicas. Todo esto, teniendo en cuenta el posible impacto que estos factores pudieran tener sobre la calidad de vida y la salud podal de los participantes del estudio.[Resumo] Introdución: O primeiro radio constitúe unha unidad funcional cuxa importancia radica no papel que desenrola nas distintas fases da marcha, sendo tamén unha peza fundamental á hora de formar o arco lonxitudinal interno, capaz de adaptarse ás irregularidades do terreno, así como de volverse unha entidade ríxida para poder propulsar o pé e o resto do corpo cara adiante. A patoloxía localizada no primeiro radio alterará a función do pé directamente, ao mesmo tempo que cursará cunha sintomatoloxía moi diversa. Porén, é imprescindible coñecer ben a anatomía deste segmento e as diferentes alteracións morfoestruturais que poideran comprometer a correcta función da estructura. Obxectivos: O obxectivo de este estudo é o de analizar mediante imaxes radiográficas distintos parámetros que poidan influír na correcta función do primeiro radio, ademáis de relacionar a presenza de diversas alteracións co impacto que poideran ter na vida cotiá dos participantes do estudo. Metodoloxía: Trátase dun estudo observacional, transversal de prevalenza realizado cunha mostra de 95 pacientes de carácter voluntaria. Desarrollarase na Clínica Universitaria de Podoloxía da UDC. A recollida de datos consistirá en analizar diferentes tipos de variables, dende variantes anropométricas, pasando por diferencias relativas ao funcionamento e á mobilidade do primeiro radio e ata parámetros medibles mediante imaxes radiolóxicas. Todo isto, tendo en conta o posible impacto que estes factores poideran ter sobre a calidade de vida e a saúde podal dos participantes do estudo.[Abstract] Introduction: The first ray constitutes a functional unit whose importance lies in the role it plays in the different march phases being also a fundamental piece when it comes to forming the internal longitudinal arch, capable of adapting to the irregularities of the terrain, as well as becoming a rigid entity to be able to propel the foot and the rest of the body forward. The pathology located in the first ray will alter the function of the foot directly, at the same time that it will occur with very diverse symptoms. Therefore, it is essential to know well the anatomy of this segment and the different morphostructural alterations that could compromise the correct function of the structure. Objectives: The objective of the study is analyze using radiographic images different parameters that can influence the correct function of the first ray, besides to relating the presence of various alterations with the impact that they could have on the study participants everyday life. Methodology: It´s an observational, cross-sectional prevalence study made with a sample formed by 95 voluntary patients. It will be developed in the University Clinic of Podiatry of the UDC. Data collection will consist of analysing different types of variables, ranging from anthropometric variants, through differences in first ray function and mobility, to parameters measurable by radiological imaging. All this, taking into account the possible impact that these factors could have on the quality of life and feet health of the study participants.Traballo fin de grao (UDC.FEP). Podoloxía. Curso 2021/202

Bayesian Gaussian network classifiers for mass spectra classification

The early diagnosis of diseases in patients is a key objective of biomedical science and one of the most important factors in the treatment of diseases such as cancer. The early detection of cancer can make the di erence between a successful treatment and the dead of the patient. Ovarian cancer is diagnosed at late clinical stage in more than 80% of patients and the 5-year survival rate is around 35% of population, while in early diagnosed patients it exceeds 90%. The aim of this work is to present techniques for the early detection of ovarian cancers based in probabilistic analysis of proteomic spectra

Effects of HCV Eradication on Bone mineral density in HIV/HCV Coinfected Patients

Little is known about the effects of eradication of HCV on bone mineral density (BMD) and biomarkers of bone remodeling in HIV/HCV coinfected patients. We prospectively assessed standardized BMD (sBMD) at the lumbar spine and femoral neck, World Health Organization (WHO) BMD categories at both sites, and plasma concentrations of soluble receptor activator of nuclear factor-kappaβ ligand (sRANKL), and osteoprotegerin (OPG) at baseline (the date of initiation of anti-HCV therapy) and at 96 weeks. A total of 238 patients were included, median age 49.5 years, 76.5% males, 48.3% with cirrhosis, 98.3% on antiretroviral therapy, median CD4+ cell count 527 cells/mm 3, 86.6% with HIV-1 RNA < 50 copies/mL. The prevalence of osteoporosis at baseline at the lumbar spine (LS) and femoral neck (FN) was 17.6% and 7.2%, respectively. Anti-HCV therapy comprised pegylated interferon and ribavirin (PegIFN-RBV) plus one direct-acting antiviral in 53.4%, PegIFN-RBV in 34.5%, and sofosbuvir/RBV in 12.2%. A total of 145 (60.9%) patients achieved sustained viral response (SVR). No significant effect of SVR was observed on sBMD for the interaction between time and SVR either in the LS (P=0.801) or the FN (P=0.911). Likewise, no significant effect of SVR was observed in plasma levels of sRANKL (P=0.205), OPG (P=0.249), and sRANKL/OPG ratio (P=0.123) for the interaction between time and SVR. No significant correlation was found between fibrosis by transient elastography, and LS and FN sBMD, at baseline, and week 96. SVR was not associated with significant changes in BMD nor biomarkers of bone remodeling in HIV/HCV-coinfected persons.This study was supported by Instituto de Salud Carlos III (ISCII), grant numbers PI11/01556, PI14/01094, PI14/01581, and PI14CIII/00011, and by Ministerio de Sanidad, Servicios Sociales e Igualdad, grant number EC11-241. The study was also funded by the RD16/0025/0017, RD16/0025/0018 and RD16CIII/0002/0002 projects as part of the Plan Nacional R + D + I and cofunded by ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER).S

Reseñas iberoamericanas

Reseñas iberoamericana

Reseñas iberoamericanas

Iberoamerican reviewsReseñas iberoamericana

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Correction: vol 7, 13205, 2016, doi:10.1038/ncomms13205Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.Peer reviewe

Personalized drug adverse side effect prediction

Les effets indésirables médicamenteux (EIM) ont des répercussions considérables tant sur la santé que sur l'économie. De 1,9% à 2,3% des patients hospitalisés en sont victimes, et leur coût a récemment été estimé aux alentours de 400 millions d'euros pour la seule Allemagne. De plus, les EIM sont fréquemment la cause du retrait d'un médicament du marché, conduisant à des pertes pour l'industrie pharmaceutique se chiffrant parfois en millions d'euros.De multiples études suggèrent que des facteurs génétiques jouent un rôle non négligeable dans la réponse des patients à leur traitement. Cette réponse comprend non seulement les effets thérapeutiques attendus, mais aussi les effets secondaires potentiels. C'est un phénomène complexe, et nous nous tournons vers l'apprentissage statistique pour proposer de nouveaux outils permettant de mieux le comprendre.Nous étudions différents problèmes liés à la prédiction de la réponse d'un patient à son traitement à partir de son profil génétique. Pour ce faire, nous nous plaçons dans le cadre de l'apprentissage statistique multitâche, qui consiste à combiner les données disponibles pour plusieurs problèmes liés afin de les résoudre simultanément.Nous proposons un nouveau modèle linéaire de prédiction multitâche qui s'appuie sur des descripteurs des tâches pour sélectionner les variables pertinentes et améliorer les prédictions obtenues par les algorithmes de l'état de l'art. Enfin, nous étudions comment améliorer la stabilité des variables sélectionnées, afin d'obtenir des modèles interprétables.Adverse drug reaction (ADR) is a serious concern that has important health and economical repercussions. Between 1.9%-2.3% of the hospitalized patients suffer from ADR, and the annual cost of ADR have been estimated to be of 400 million euros in Germany alone. Furthermore, ADRs can cause the withdrawal of a drug from the market, which can cause up to millions of dollars of losses to the pharmaceutical industry.Multiple studies suggest that genetic factors may play a role in the response of the patients to their treatment. This covers not only the response in terms of the intended main effect, but also % according toin terms of potential side effects. The complexity of predicting drug response suggests that machine learning could bring new tools and techniques for understanding ADR.In this doctoral thesis, we study different problems related to drug response prediction, based on the genetic characteristics of patients.We frame them through multitask machine learning frameworks, which combine all data available for related problems in order to solve them at the same time.We propose a novel model for multitask linear prediction that uses task descriptors to select relevant features and make predictions with better performance as state-of-the-art algorithms. Finally, we study strategies for increasing the stability of the selected features, in order to improve interpretability for biological applications

Anàlisi del portal de transparència de l'Ajuntament de Gandía

[ES] El presente trabajo de final de grado se centra en el análisis del portal de transparencia del ayuntamiento de Gandía. El objetivo principal es evaluar la implementación y eficacia de este portal en términos de acceso a la información, cumplimiento de requisitos legales y participación ciudadana. El estudio incluye una descripción detallada del portal, su estructura, funcionalidades y usabilidad. Se utiliza una metodología de investigación adecuada para recopilar datos y realizar un examen exhaustivo. Los resultados y conclusiones obtenidos sirven como base para ofrecer recomendaciones destinadas a mejorar el portal de transparencia.[EN] This undergraduate thesis focuses on the analysis of the transparency portal of the city council of Gandía. The main objective is to evaluate the implementation and effectiveness of this portal in terms of information access, compliance with legal requirements and citizen participation. The study includes a detailed description of the portal, its structure, funcionalities and usability. An appropriate research methodology will be employed to gather data and conduct a comprehensive analysis. The results and conclusions obtained serve as a basis for providing recommendations aimed at improving the transparency portal.Bellón Carbonell, V. (2023). Análisis del portal de transparencia del Ayuntamiento de Gandía. Universitat Politècnica de València. http://hdl.handle.net/10251/19811

Prédiction personalisée des effets secondaires indésirables de médicaments

Adverse drug reaction (ADR) is a serious concern that has important health and economical repercussions. Between 1.9%-2.3% of the hospitalized patients suffer from ADR, and the annual cost of ADR have been estimated to be of 400 million euros in Germany alone. Furthermore, ADRs can cause the withdrawal of a drug from the market, which can cause up to millions of dollars of losses to the pharmaceutical industry.Multiple studies suggest that genetic factors may play a role in the response of the patients to their treatment. This covers not only the response in terms of the intended main effect, but also % according toin terms of potential side effects. The complexity of predicting drug response suggests that machine learning could bring new tools and techniques for understanding ADR.In this doctoral thesis, we study different problems related to drug response prediction, based on the genetic characteristics of patients.We frame them through multitask machine learning frameworks, which combine all data available for related problems in order to solve them at the same time.We propose a novel model for multitask linear prediction that uses task descriptors to select relevant features and make predictions with better performance as state-of-the-art algorithms. Finally, we study strategies for increasing the stability of the selected features, in order to improve interpretability for biological applications.Les effets indésirables médicamenteux (EIM) ont des répercussions considérables tant sur la santé que sur l'économie. De 1,9% à 2,3% des patients hospitalisés en sont victimes, et leur coût a récemment été estimé aux alentours de 400 millions d'euros pour la seule Allemagne. De plus, les EIM sont fréquemment la cause du retrait d'un médicament du marché, conduisant à des pertes pour l'industrie pharmaceutique se chiffrant parfois en millions d'euros.De multiples études suggèrent que des facteurs génétiques jouent un rôle non négligeable dans la réponse des patients à leur traitement. Cette réponse comprend non seulement les effets thérapeutiques attendus, mais aussi les effets secondaires potentiels. C'est un phénomène complexe, et nous nous tournons vers l'apprentissage statistique pour proposer de nouveaux outils permettant de mieux le comprendre.Nous étudions différents problèmes liés à la prédiction de la réponse d'un patient à son traitement à partir de son profil génétique. Pour ce faire, nous nous plaçons dans le cadre de l'apprentissage statistique multitâche, qui consiste à combiner les données disponibles pour plusieurs problèmes liés afin de les résoudre simultanément.Nous proposons un nouveau modèle linéaire de prédiction multitâche qui s'appuie sur des descripteurs des tâches pour sélectionner les variables pertinentes et améliorer les prédictions obtenues par les algorithmes de l'état de l'art. Enfin, nous étudions comment améliorer la stabilité des variables sélectionnées, afin d'obtenir des modèles interprétables