Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients:a multicenter machine learning study with highly granular data from the Dutch Data Warehouse

Background: The identification of risk factors for adverse outcomes and prolonged intensive care unit (ICU) stay in COVID-19 patients is essential for prognostication, determining treatment intensity, and resource allocation. Previous studies have determined risk factors on admission only, and included a limited number of predictors. Therefore, using data from the highly granular and multicenter Dutch Data Warehouse, we developed machine learning models to identify risk factors for ICU mortality, ventilator-free days and ICU-free days during the course of invasive mechanical ventilation (IMV)... Mehr ...

Dokumenttyp: Artikel
Erscheinungsdatum: 2021
Reihe/Periodikum: on behalf of Dutch ICU Data Sharing Against COVID-19 Collaborators 2021 , ' Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients : a multicenter machine learning study with highly granular data from the Dutch Data Warehouse ' , Intensive Care Medicine Experimental , vol. 9 , 32 , pp. 1-15 . https://doi.org/10.1186/s40635-021-00397-5
Schlagwörter: COVID-19 / Machine learning / Mortality prediction / Risk factors / /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being / name=SDG 3 - Good Health and Well-being
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27463588
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://research.vu.nl/en/publications/806fe578-5655-46e5-bfba-62c6341a014f