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Prognosis and Management of Infective Endocarditis Using the Clinical Data Warehouse From AP-HP
"Infective endocarditis (IE) is a rare but severe condition with significant morbidity and mortality, with in-hospital mortality reaching 20% and 1-year mortality up to 40%. The epidemiological profile of IE has profoundly changed in recent years, both in terms of responsible microorganisms and affected populations, shifting from young adults with post-rheumatic valvulopathy to older populations with degenerative valve disease or prosthetic implants. Prophylaxis and management recommendations have also evolved, underscoring the importance of monitoring the evolution of IE profiles in France. Despite these changes, there is no standardized surveillance for IE in France, and existing studies often rely on data from specialized centers, introducing selection biases. Moreover, another important limitation when studying IE using medical-administrative basis, like the french nationwide claims database (SNDS), is the poor performances of administrative coding (ICD-10) in accurately identifying IE cases. The ""ENDO-EDS"" project aims to leverage the extensive data available in the APHP Clinical Data Warehouse (CDW) to study IE in a real-world, unbiased context. Indeed, the AP-HP clinical data warehouse, with 11 million patients, offers the opportunity to identify IE cases across a large population base and, due to the presence of both expert and non-expert IE hospitals, to describe the characteristics of the disease while reducing bias risks. In addition, AP-HP CDW contains medical reports and other documents emitted during patient' stays in hospital, thus enabling to overcome ICD-10 coding limitations, by utilizing a large-scale clinical data repository combined with advanced Natural Language Processing (NLP) algorithms. The anticipated benefits include improving knowledge of the epidemiological profile of IE, describing diagnostic and therapeutic management practices, and studying their impact on patient prognosis. These efforts aim to contribute to the improvement of
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