Development and validation of a prediction model for 30-day mortality in hospitalised patients with COVID-19: the COVID-19 SEIMC score

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• dc.contributor.author Berenguer, Juan
• dc.contributor.author Borobia, Alberto M.
• dc.contributor.author Ryan, Pablo
• dc.contributor.author Rodríguez Baño, Jesús
• dc.contributor.author Bellón, José M.
• dc.contributor.author Jarrín, Inmaculada
• dc.contributor.author Carratalà, Jordi
• dc.contributor.author Pachón, Jerónimo
• dc.contributor.author Carcas, Antonio J.
• dc.contributor.author Yllescas, María
• dc.contributor.author Arribas, José Ramón
• dc.date.accessioned 2022-09-28T07:15:47Z
• dc.date.available 2022-09-28T07:15:47Z
• dc.date.issued 2021
• dc.description.abstract Objective: to develop and validate a prediction model of mortality in patients with COVID-19 attending hospital emergency rooms. Design: Multivariable prognostic prediction model. Setting: 127 Spanish hospitals. Participants: derivation (DC) and external validation (VC) cohorts were obtained from multicentre and single-centre databases, including 4035 and 2126 patients with confirmed COVID-19, respectively. Interventions: prognostic variables were identified using multivariable logistic regression. Main outcome measures: 30-day mortality. Results: patients' characteristics in the DC and VC were median age 70 and 61 years, male sex 61.0% and 47.9%, median time from onset of symptoms to admission 5 and 8 days, and 30-day mortality 26.6% and 15.5%, respectively. Age, low age-adjusted saturation of oxygen, neutrophil-to-lymphocyte ratio, estimated glomerular filtration rate by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, dyspnoea and sex were the strongest predictors of mortality. Calibration and discrimination were satisfactory with an area under the receiver operating characteristic curve with a 95% CI for prediction of 30-day mortality of 0.822 (0.806-0.837) in the DC and 0.845 (0.819-0.870) in the VC. A simplified score system ranging from 0 to 30 to predict 30-day mortality was also developed. The risk was considered to be low with 0-2 points (0%-2.1%), moderate with 3-5 (4.7%-6.3%), high with 6-8 (10.6%-19.5%) and very high with 9-30 (27.7%-100%). Conclusions: a simple prediction score, based on readily available clinical and laboratory data, provides a useful tool to predict 30-day mortality probability with a high degree of accuracy among hospitalised patients with COVID-19.
• dc.format.mimetype application/pdf
• dc.identifier.citation Berenguer J, Borobia AM, Ryan P, Rodríguez-Baño J, Bellón JM, Jarrín I, et al. Development and validation of a prediction model for 30-day mortality in hospitalised patients with COVID-19: the COVID-19 SEIMC score. Thorax. 2021 Sep; 76(9): 920-9. DOI: 10.1136/thoraxjnl-2020-216001
• dc.identifier.doi http://dx.doi.org/10.1136/thoraxjnl-2020-216001
• dc.identifier.issn 0040-6376
• dc.identifier.uri http://hdl.handle.net/10230/54190
• dc.language.iso eng
• dc.publisher BMJ Publishing Group
• dc.rights Copyright © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0
• dc.subject.keyword Clinical epidemiology
• dc.subject.keyword Critical care
• dc.subject.keyword Emergency medicine
• dc.subject.keyword Pneumonia
• dc.subject.keyword Respiratory infection
• dc.subject.keyword Viral infection
• dc.title Development and validation of a prediction model for 30-day mortality in hospitalised patients with COVID-19: the COVID-19 SEIMC score
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion