RESUMEN
BACKGROUND: Systematic reviews allow health decisions to be informed by the best available research evidence. However, their number is proliferating quickly, and many skills are required to identify all the relevant reviews for a specific question. METHODS AND FINDINGS: We screen 10 bibliographic databases on a daily or weekly basis, to identify systematic reviews relevant for health decision-making. Using a machine-based approach developed for this project we select reviews, which are then validated by a network of more than 1000 collaborators. After screening over 1,400,000 records we have identified more than 300,000 systematic reviews, which are now stored in a single place and accessible through an easy-to-use search engine. This makes Epistemonikos the largest database of its kind. CONCLUSIONS: Using a systematic approach, recruiting a broad network of collaborators and implementing automated methods, we developed a one-stop shop for systematic reviews relevant for health decision making.
Asunto(s)
Atención a la Salud , Motor de Búsqueda , Bases de Datos Bibliográficas , Bases de Datos Factuales , Humanos , Revisiones Sistemáticas como AsuntoRESUMEN
Introduction: The evidence on COVID-19 is being produced at high speed, so it is challenging for decision-makers to keep up. It seems appropriate, then, to put into practice a novel approach able to provide the scientific community and other interested parties with quality evidence that is actionable, and rapidly and efficiently produced. Methods and analysis: We designed a protocol for multiple parallel systematic reviews and overviews of systematic reviews in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P). We will search for primary studies and systematic reviews that answer different questions related to COVID-19 using both a centralized repository (Epistemonikos database) and a manual search in MEDLINE/PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials. We will also search for literature in several other sources. At least two researchers will independently undertake the selection of studies, data extraction, and assessment of the quality of the included studies. We will synthesize data for each question using meta-analysis, when possible, and we will prepare Summary of Findings tables according to the GRADE approach. All the evidence will be organized in an open platform (L·OVE - Living OVerview of Evidence) that will be continuously updated using artificial intelligence and a broad network of experts. Ethics and dissemination: No ethics approval is considered necessary. The results of these articles will be widely disseminated via peer-reviewed publications, social networks, and traditional media, and will be sent to relevant international organizations discussing this topic.
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Betacoronavirus , Infecciones por Coronavirus , Medicina Basada en la Evidencia , Almacenamiento y Recuperación de la Información , Pandemias , Neumonía Viral , Revisiones Sistemáticas como Asunto , Acceso a la Información , Inteligencia Artificial , COVID-19 , Humanos , Metaanálisis como Asunto , Proyectos de Investigación , SARS-CoV-2RESUMEN
Este trabajo, dedicado a la novela Madame Bovary de Gustave Flaubert, analiza la histeria de Emma Bovary mediante una redescripción de su caso en el vocabulario de Jacques Lacan. A partir de estudios de Juan David Nasio (2000) y Joël Dor (2000), se hace una lectura detallada de las relaciones amorosas de Emma Bovary, para buscar en ellas las articulaciones de su deseo histérico
This article studies Gustave Flauberts novel Madame Bovary, analysing Emma Bovarys hysteria by means of a redescription of her clinical case in the vocabulary of Jacques Lacan. Starting from contributions to the Lacanian theory of hysteria by Juan David Nasio (2000) and Joël Dor (2000), the article provides a close reading of Emmas love affairs the main site where to observe the dynamics of her hysterical desire