Development and validation of a prediction model for 30-day mortality in hospitalised patients with COVID-19: The COVID-19 SEIMC score
Entity
UAM. Departamento de Farmacología; UAM. Departamento de MedicinaPublisher
BmjDate
2021-09-01Citation
10.1136/thoraxjnl-2020-216001
Thorax 76.9 (2021): 920-929
ISSN
0040-6376 (print); 1468-3296 (online)DOI
10.1136/thoraxjnl-2020-216001Editor's Version
https://doi.org/10.1136/thoraxjnl-2020-216001Subjects
Pneumonia; Tool; Viral infection; Critical care; Emergency medicine; Clinical epidemiology; Individual prognosis; Respiratory infection; Diagnosis tripod; MedicinaRights
© Author(s) (or their employer(s)) 2021Abstract
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
Files in this item
Google Scholar:Berenguer, Juan
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Borobia Pérez, Alberto M.
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Ryan, Pablo
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Rodríguez-Baño, Jesús
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Bellón, Jose M.
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Jarrín, Inmaculada
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Carratalà, Jordi
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Pachón, Jerónimo
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Carcas Sansuán, Antonio Javier
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Yllescas, María
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Arribas López, José Ramón
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