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The SARS-CoV-2 virus enters host cells after binding to the angiotensin-converting enzyme 2 (ACE2), but whether renin\u2212angiotensin\u2212aldosterone system inhibitors (RAASi) are beneficial remains controversial. Standard statistical approaches may fail in assessing medications effects, due to multiple sources of bias in COVID-19 case series collected on an emergency basis. We present a data-driven approach to tackle these challenges. Multilayer risk stratifications were derived for assessing drugs effect, while Bayesian networks were estimated, to analyze dependencies among risk factors\u2019 and treatments\u2019 impact on survival. We provide strong evidence for protectivity of RAASi on hospitalized patients that call for randomized controlled trials of RAASi as COVID-19 treatment option.<\/jats:p>","DOI":"10.1073\/pnas.2016877118","type":"journal-article","created":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T16:48:28Z","timestamp":1607618908000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":33,"title":["A data-driven approach to identify risk profiles and protective drugs in COVID-19"],"prefix":"10.1073","volume":"118","author":[{"given":"Pietro E.","family":"Cipp\u00e0","sequence":"first","affiliation":[{"name":"Department of Medicine, Division of Nephrology, Ente Ospedaliero Cantonale, 6500 Bellinzona, Switzerland;"},{"name":"Faculty of Medicine, University of Zurich, 8006 Zurich, 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