38 research outputs found

    Rheumatic Diseases: Pathophysiology, Targeted Therapy, Focus on Vascular and Pulmonary Manifestations

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    This e-book summarises the latest advances in the rheumatic diseases with a focus on the recent efforts of vascular and pulmonary manifestations and anticipate the new and future directions of these research topic. Rheumatic diseases represent a heterogeneous group of severe autoimmune disorders. The present Special Issue aims to provide an overview of the complexity of vascular and pulmonary manifestations of rheumatologic diseases and helps in knowledge to manage them. The eleven published articles here collected underline the complexity of rheumatic diseases and the difficult to treated them. The manuscripts provide an overview of the pathophysiology and current treatment regimes of these disorders, highlighting tools which assist with diagnosis, risk stratification and therapy. Finally, we underline the importance of a multidisciplinary team working using the skills of clinicians, radiologists, and pathologists

    Rheumatic Diseases: Pathophysiology, Targeted Therapy, Focus on Vascular and Pulmonary Manifestations

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    This book aims to summarize the latest advances in the rheumatic diseases, particularly regarding their pathophysiology and targeted therapy, with a focus on the recent efforts of vascular and pulmonary manifestations in order to anticipate new and future directions of these research topics. Rheumatic diseases represent a heterogeneous group of severe autoimmune disorders. The present Special Issue aims to provide an overview of the diversity and complexity of vascular and pulmonary manifestations of rheumatic diseases and to highlight gaps in our knowledge of how to effectively manage them. Despite their significant morbidity, we have a limited understanding of their pathogenesis. The eleven published articles reported here underline the complexity of rheumatic diseases and the difficulty of managing them. The manuscripts provide an overview of the pathophysiology and current management approach of these disorders, highlighting tools that assist with diagnosis, risk stratification, and therapy. A significant number of articles have reported innovative and effective treatments for the most frequent and debilitating complications of rheumatic diseases. The book emphasizes the importance of multidisciplinary teams using the skills of laboratory researchers, clinicians, radiologists, and pathologists. Furthermore, recent findings are presented and discussed, highlighting strategies to combat worsening symptoms of rheumatic diseases. The research described in this book provide an extremely useful example of the results achieved in the field of anti-rheumatic drug development. Detailed information on new breakthroughs can be found in this book. We strongly encourage a wide group of readers to explore the book that we are presenting for inspiration to develop new approaches to the diagnosis and treatment of rheumatic diseases

    Clinical Utility of Applying PGx and Deprescribing-Based Decision Support in Polypharmacy

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    Polypharmacy is a necessary and important aspect of drug treatment; however, it becomes a challenge when the medication risks outweigh the benefits for an individual patient. Drug–drug interactions and the introduction of prescribing cascades are common features of polypharmacy, which can lead to ineffectiveness and increased risk of adverse drug reactions (ADR). Genes encoding CYP450 isozymes and other drug-related biomarkers have attracted considerable attention as targets for pharmacogenetic (PGx) testing due to their impact on drug metabolism and response. This Special Issue is devoted to explore the status and initiatives taken to circumvent ineffectiveness and to improve medication safety for polypharmacy patients. Specific areas include drug–drug interactions and consequences thereof in therapeutic management, including PK- and PD-profiling; the application of PGx-based guidance and/or decision tools for drug–gene and drug–drug gene interactions; medication reviews; development and application of deprescribing tools; and drivers and barriers to overcome for successful implementation in the healthcare system

    Developing artificial intelligence and machine learning to support primary care research and practice

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    This thesis was motivated by the potential to use everyday data , especially that collected in electronic health records (EHRs) as part of healthcare delivery, to improve primary care for clients facing complex clinical and/or social situations. Artificial intelligence (AI) techniques can identify patterns or make predictions with these data, producing information to learn about and inform care delivery. Our first objective was to understand and critique the body of literature on AI and primary care. This was achieved through a scoping review wherein we found the field was at an early stage of maturity, primarily focused on clinical decision support for chronic conditions in high-income countries, with low levels of primary care involvement and model evaluation in real-world settings. Our second objective was to demonstrate how AI methods can be applied to problems in descriptive epidemiology. To achieve this, we collaborated with the Alliance for Healthier Communities, which provides team-based primary health care through Community Health Centres (CHCs) across Ontario to clients who experience barriers to regular care. We described sociodemographic, clinical, and healthcare use characteristics of their adult primary care population using EHR data from 2009-2019. We used both simple statistical and unsupervised learning techniques, applied with an epidemiological lens. In addition to substantive findings, we identified potential avenues for future learning initiatives, including the development of decision support tools, and methodological considerations therein. Our third objective was to advance interpretable AI methodology that is well-suited for heterogeneous data, and is applicable in clinical epidemiology as well as other settings. To achieve this, we developed a new hybrid feature- and similarity-based model for supervised learning. There are two versions, fit by convex optimization with a sparsity-inducing penalty on the kernel (similarity) portion of the model. We compared our hybrid models with solely feature- and similarity-based approaches using synthetic data and using CHC data to predict future loneliness or social isolation. We also proposed a new strategy for kernel construction with indicator-coded data. Altogether, this thesis progressed AI for primary care in general and for a particular health care organization, while making research contributions to epidemiology and to computer science

    Wearable Sensors Applied in Movement Analysis

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    Recent advances in electronics have led to sensors whose sizes and weights are such that they can be placed on living systems without impairing their natural motion and habits. They may be worn on the body as accessories or as part of the clothing and enable personalized mobile information processing. Wearable sensors open the way for a nonintrusive and continuous monitoring of body orientation, movements, and various physiological parameters during motor activities in real-life settings. Thus, they may become crucial tools not only for researchers, but also for clinicians, as they have the potential to improve diagnosis, better monitor disease development and thereby individualize treatment. Wearable sensors should obviously go unnoticed for the people wearing them and be intuitive in their installation. They should come with wireless connectivity and low-power consumption. Moreover, the electronics system should be self-calibrating and deliver correct information that is easy to interpret. Cross-platform interfaces that provide secure data storage and easy data analysis and visualization are needed.This book contains a selection of research papers presenting new results addressing the above challenges

    Clinical Applications of Pharmacogenetics

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    The rapidly evolving field of Pharmacogenetics aims at identifying the genetic factors implicated in the inter-individual variation of drug response. These factors could enable patient sub-classification based on their treatment needs thus expediting drug development and promoting personalized, safer and more effective treatments. This book presents Pharmacogenetic examples from a broad spectrum of different drugs, for different diseases, which are representative of different stages of evaluation or application. It has been designed so as to serve both the unfamiliar reader through explanations of basic Pharmacogenetic concepts, the clinician with presentation of the latest developments and international guidelines, and the research scientist with examples of Pharmacogenetic applications, discussions on the limitations and an outlook on the new scientific trends in this field

    Multimorbilidad, fragilidad y resultados en salud en población geriátrica

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    Antecedentes y objetivosLa multimorbilidad, definida como la presencia de dos o más enfermedades crónicas de forma simultánea en un individuo, y la fragilidad, es decir el estado de vulnerabilidad ante factores estresantes, tienen un gran impacto en la salud de los pacientes y en el uso de los recursos sanitarios. El objetivo general de esta tesis que se presenta es avanzar en el conocimiento de la epidemiología de la multimorbilidad en pacientes geriátricos y su impacto sobre los resultados en salud (interacción con la dependencia funcional, la mortalidad y la utilización de servicios sanitarios), basándonos en el análisis de grandes bases de datos clínico-administrativas de la población de Aragón. Las preguntas de investigación se responden en cuatro artículos publicados y vinculados a cada uno de los siguientes objetivos específicos: a) explorar la multimorbilidad en población geriátrica hospitalizada, b) caracterizar la población geriátrica centenaria de Aragón, c) definir las variables demográficas y clínicas que diferencian a los centenarios de los ancianos más jóvenes de Aragón y d) analizar la utilidad de la armonización de bases de datos en la caracterización de la población geriátrica con multimorbilidad y fragilidad en Europa.MetodologíaEl primer objetivo específico se abordó a través de análisis factorial exploratorio de los diagnósticos crónicos y síndromes geriátricos para la identificación de patrones de multimorbilidad, basado en correlaciones tetracóricas, debido a la naturaleza dicotómica (presencia/ausencia) de la variable diagnóstica. Análisis estratificado por grupos de edad y sexo.El segundo y tercer objetivos específicos se abordó mediante un estudio observacional retrospectivo en la Cohorte EpiChron (Aragón). Análisis de las características sociodemográficas, clínicas, consumo de fármacos y utilización de servicios sanitarios, utilizando información de historia clínica electrónica y bases de datos clínico-administrativas. Los resultados se han calculado como medias y/o frecuencias con intervalo de confianza del 95%. Para el análisis de diferencias por sexo, se ha utilizado el test de Kruskal-Wallis para comparar las medias y el test Chi-cuadrado de Pearson para comparar frecuencias. La significación estadística se ha establecido en pEl cuarto objetivo se abordó a través de un estudio descriptivo para valorar la capacidad de armonización de 4 bases de datos sobre salud en personas mayores.ConclusionesEl patrón de multimorbilidad dependencia inducida, compuesto exclusivamente por síndromes geriátricos, puede actuar como desencadenante del deterioro funcional, lo que subraya la importancia de la evaluación global de los pacientes geriátricos. La multimorbilidad parece ser la regla más que la excepción en esta población, que presenta principalmente un patrón cardiocerebrovascular. Abordar la atención médica en las personas mayores desde una perspectiva geriátrica integral es fundamental para preservar su salud y evitar los efectos negativos de la polifarmacia. El estado de salud aparentemente mejor en los centenarios que en nonagenarios y octogenarios, deja la puerta abierta para reconocer que esta población muere más como consecuencia de un mecanismo de envejecimiento biológico natural que por la presencia de enfermedades específicas. La identificación de factores potenciales para una longevidad excepcional requeriría más estudios longitudinales multidisciplinarios que deberían analizar simultáneamente información clínica, bioquímica y de estilo de vida.La aplicación de metodologías comunes de registro de información, facilita la armonización, la fusión de datos, la extrapolación a otros contextos y la posibilidad de trabajar de forma conjunta en múltiples campos de la geriatría. <br /

    Association between number of medications and mortality in geriatric inpatients : a Danish nationwide register-based cohort study

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    Purpose: To explore the association between the number of medications and mortality in geriatric inpatients taking activities of daily living and comorbidities into account. Methods: A nationwide population-based cohort study was performed including all patients aged C65 years admitted to geriatric departments in Denmark during 2005-2014. The outcome of interest was mortality. Activities of daily living using Barthel-Index (BI) were measured at admission. National health registers were used to link data on an individual level extracting data on medications, and hospital diseases. Patients were followed to the end of study (31.12.2015), death, or emigration, which ever occurred first. Kaplan-Meier survival curves were used to estimate crude survival proportions. Univariable and multivariable analyses were performed using Cox regression. The multivariable analysis adjusted for age, marital status, period of hospital admission, BMI, and BI (model 1), and further adding either number of diseases (model 2) or Charlson comorbidity index (model 3). Results: We included 74603 patients (62.8% women), with a median age of 83 (interquartile range [IQR] 77-88) years. Patients used a median of 6 (IQR 4-9) medications. Increasing number of medications was associated with increased overall, 30-days, and 1-year mortality in all 3 multivariable models for both men and women. For each extra medication the mortality increased by 3% in women and 4% in men in the fully adjusted model. Conclusion: Increasing number of medications was associated with mortality in this nationwide cohort of geriatric inpatients. Our findings highlight the importance of polypharmacy in older patients with comorbidities

    Co-occurrence patterns in diagnostic data

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    We demonstrate how graph decomposition techniques can be employed for the visualization of hierarchical co-occurrence patterns between medical data items. Our research is based on Gaifman graphs (a mathematical concept introduced in Logic), on specific variants of this concept, and on existing graph decomposition notions, specifically, graph modules and the clan decomposition of so-called 2-structures. The construction of the Gaifman graphs from a dataset is based on co-occurrence, or lack of it, of items in the dataset. We may select a discretization on the edge labels to aim at one among several Gaifman graph variants. Then, the decomposition of the graph may provide us with visual information about the data co-occurrences, after which one can proceed to more traditional statistical analysis.Partially supported by European Research Council (ERC) under the European Union's Horizon2020 research and innovation programme, grant agreement ERC-2014-CoG 648276 (AUTAR);by grant TIN2017-89244-R from Ministerio de Economia, Industria y Competitividad, and byConacyt (México). We acknowledge unfunded recognition 2017SGR-856 (MACDA) from AGAUR(Generalitat de Catalunya).Peer ReviewedPostprint (published version

    Model-based simulations of drug-drug interactions in the Swiss HIV Cohort Study

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