English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/216395
Share/Impact:
Statistics
logo share SHARE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE
Exportar a otros formatos:

Title

COVID-19 Mortality Risk Assessment: An International Multi-Center Study

AuthorsBertsimas, Dimitris; Lukin, Galit; Mingardi, Luca; Nohadani, Omid; Orfanoudaki, Agni; Stellato, Bartolomeo; Wiberg, Holly; González-García, Sara ; Parra-Calderón, Carlos Luis; The Hellenic COVID-19 Study Group; Robinson, Kenneth; Schneider, Michelle; Stein, Barry; Estirado, Alberto; Beccara, Lia a; Canino, Rosario; Bello, Martina Dal; Pezzetti, Federica; Pan, Angelo
Issue Date9-Jul-2020
PublisherMedRxiv
AbstractBackground: Timely identification of COVID-19 patients at high risk of mortality can significantly improve patient management and resource allocation within hospitals. This study seeks to develop and validate a data-driven personalized mortality risk calculator for hospitalized COVID-19 patients.
Methods: De-identified data was obtained for 3,927 COVID-19 positive patients from six independent centers, comprising 33 different hospitals. Demographic, clinical, and laboratory variables were collected at hospital admission. The COVID-19 Mortality Risk (CMR) tool was developed using the XGBoost algorithm to predict mortality. Its discrimination performance was subsequently evaluated on three validation cohorts.
Findings: The derivation cohort of 3,062 patients has an observed mortality rate of 26.84%. Increased age, decreased oxygen saturation (≤ 93%), elevated levels of C-reactive protein (≥ 130 mg/L), blood urea nitrogen (≥ 18 mg/dL), and blood creatinine (≥ 1.2 mg/dL) were identified as primary risk factors, validating clinical findings. The model obtains out-ofsample AUCs of 0.90 (95% CI, 0.87-0.94) on the derivation cohort. In the validation cohorts, the model obtains AUCs of 0.92 (95% CI, 0.88-0.95) on Seville patients, 0.87 (95% CI, 0.84- 0.91) on Hellenic COVID-19 Study Group patients, and 0.81 (95% CI, 0.76-0.85) on Hartford Hospital patients. The CMR tool is available as an online application at covidanalytics.io/mortality_calculator and is currently in clinical use.
Interpretation: The CMR model leverages machine learning to generate accurate mortality predictions using commonly available clinical features. This is the first risk score trained and validated on a cohort of COVID-19 patients from Europe and the United States.
Publisher version (URL)https://doi.org/10.1101/2020.07.07.20148304
URIhttp://hdl.handle.net/10261/216395
DOIhttp://dx.doi.org/10.1101/2020.07.07.20148304
Appears in Collections:(IBIS) Artículos
(VICYT) Colección Especial COVID-19
Files in This Item:
File Description SizeFormat 
COVID19 Mortality Risk Assessment.pdf1,13 MBAdobe PDFThumbnail
View/Open
Show full item record
Review this work
 


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.