Artículo
Development and validation of a prediction model for 30-day mortality in hospitalised patients with COVID-19: the COVID-19 SEIMC score
Autor/es | Berenguer, Juan
Borobia, Alberto M. Ryan, Pablo Rodríguez-Baño, Jesús Bellón, José M. Jarrín, Inmaculada Carratalà, Jordi Pachón Díaz, Jerónimo Carcas, Antonio J. Yllescas, María Arribas, José Ramón |
Fecha de publicación | 2021 |
Fecha de depósito | 2022-10-06 |
Publicado en |
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Resumen | 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.
P ... 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. |
Identificador del proyecto | (RIS) (RD16/0025/0017 (JB)
RD16/0025/0018 (JRA) RD16CIII/0002/0006 (IJ)) (REIPI) (RD16/0016/0001 (JRB) RD16/0016/0005 (JC) RD16/0016/0009 (JP)) |
Cita | Berenguer, J., Borobia, A.M., Ryan, P., Rodríguez-Baño, J., Bellón, J.M., Jarrín, I.,...,Arribas, J.R. (2021). Development and validation of a prediction model for 30-day mortality in hospitalised patients with COVID-19: the COVID-19 SEIMC score. Thorax, 76 (9), 920-929. https://doi.org/doi:10.1136/thoraxjnl-2020-216001. |
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