Development and validation of a prediction model for 30-day mortality in hospitalised patients with COVID-19: The COVID-19 SEIMC score
EntityUAM. Departamento de Farmacología; UAM. Departamento de Medicina
10.1136/thoraxjnl-2020-216001Thorax 76.9 (2021): 920-929
ISSN0040-6376 (print); 1468-3296 (online)
SubjectsPneumonia; Tool; Viral infection; Critical care; Emergency medicine; Clinical epidemiology; Individual prognosis; Respiratory infection; Diagnosis tripod; Medicina
Rights© Author(s) (or their employer(s)) 2021
Esta obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial 4.0 Internacional.
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
Google Scholar:Berenguer, Juan - Borobia Pérez, Alberto M. - Ryan, Pablo - Rodríguez-Baño, Jesús - Bellón, Jose M. - Jarrín, Inmaculada - Carratalà, Jordi - Pachón, Jerónimo - Carcas Sansuán, Antonio Javier - Yllescas, María - Arribas López, José Ramón
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