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Performance of the CURB-65, SOFA, NEWS2, and 4C Mortality Score scales to predict in-hospital mortality from COVID-19 within the first 30 days in Lima, Peru
Capacidad de las escalas CURB-65, SOFA, NEWS2 y 4C para predecir la mortalidad hospitalaria por COVID-19 en los primeros 30 días en Lima, Perú
DOI:
https://doi.org/10.15446/revfacmed.v72n1.109524Palabras clave:
COVID-19, Coronavirus, Mortality, Pneumonia, Prognosis (en)COVID-19, Coronavirus, Mortalidad, Neumonía, Predicción (es)
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Introduction: Although the COVID-19 pandemic has been contained, new and fatal variants causing a high inflammatory response could emerge. Therefore, the use of instruments that allow healthcare workers to identify potentially severe patients is relevant.
Objective: To determine the performance of the CURB-65, SOFA, NEWS2, and 4C Mortality Score scales in predicting in-hospital mortality due to COVID-19 within the first 30 days in Lima, Peru.
Materials and methods: Retrospective analytical study conducted in 268 adults with COVID-19 pneumonia hospitalized between January 1 and June 30, 2021, in a tertiary care hospital in Lima, Peru. To determine the prediction performance of in-hospital mortality within the first 30 days due to COVID-19, the ROC (receiver operating characteristic) curves and areas under the curve (AUC) of each scale were calculated, as well as their sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The score cut-off points were obtained using the Youden index.
Results: The median age of the participants was 54 years (IQR: 45.20-64.00), 177 (66.04%) were male, and 67 (25.00%) died. The score with the highest AUC was the 4C Mortality Score (0.89; 95%CI: 0.84-0.93), followed by the SOFA (0.87; 95%CI: 0.83-0.92).
Conclusions: All four scales had an acceptable predictive performance for in-hospital mortality in patients with COVID-19, and the 4C Mortality Score had the best performance, followed by the SOFA.
Introducción. A pesar de que la pandemia por COVID-19 ha sido controlada, podrían surgir nuevas y fatales variantes que generen una respuesta inflamatoria alta. Por tanto, resulta pertinente el uso de instrumentos que permitan al personal sanitario identificar pacientes potencialmente graves.
Objetivo. Determinar la capacidad de las escalas CURB-65, SOFA, NEWS2 y 4C Mortality Score para predecir la mortalidad hospitalaria por COVID-19 en los primeros 30 días en Lima, Perú.
Materiales y métodos. Estudio analítico retrospectivo realizado en 268 adultos con neumonía por COVID-19 hospitalizados entre enero 1 y junio 30 del 2021 en un hospital de tercer nivel de atención en Lima, Perú. Para determinar el rendimiento de predicción de mortalidad hospitalaria por COVID-19 dentro de los primeros 30 días, se calcularon las curvas ROC (Operativa del receptor) y las áreas bajo la curva (AUC) de cada escala, así como su sensibilidad, especificidad, valor predictivo positivo (VPP) y valor predictivo negativo (VPN). Los puntos de corte de puntaje de las escalas se obtuvieron mediante el índice de Youden.
Resultados. La mediana de edad de los participantes fue de 54 años (RIQ: 45.20-64.00), 177 (66.04%) eran hombres y 67 (25.00%) fallecieron. La escala con el mayor AUC fue la 4C Mortality Score (0.89; IC95%: 0.84-0.93), seguida de la SOFA (0.87; IC95%: 0.83-0.92).
Conclusiones. Las cuatro escalas tuvieron una aceptable capacidad predictiva de mortalidad hospitalaria en pacientes con COVID-19, siendo la 4C Mortality Score la que tuvo el mejor rendimiento, seguida de la SOFA.
Referencias
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