%0 Journal Article
%@ 2045-2322
%A de Santos Castro, Pedro Ángel
%A del Pozo Vegas, Carlos
%A Pinilla Arribas, Leyre Teresa
%A Zalama Sánchez, Daniel
%A Sanz-García, Ancor
%A Vásquez del Águila, Tony Giancarlo
%A González Izquierdo, Pablo
%A de Santos Sánchez, Sara
%A Mazas Pérez-Oleaga, Cristina
%A Dominguez Azpíroz, Irma
%A Elío Pascual, Iñaki
%A Martín-Rodríguez, Francisco
%D 2024
%F uniromana:15624
%J Scientific Reports
%K COVID-19 pandemic, Scoring systems, 4C mortality score, SEIMC score, Mortality, Emergency department
%N 1
%T Performance of the 4C and SEIMC scoring systems in predicting mortality from onset to current COVID-19 pandemic in emergency departments
%U http://repositorio.uniromana.edu.do/id/eprint/15624/
%V 14
%X The evolution of the COVID-19 pandemic has been associated with variations in clinical presentation and severity. Similarly, prediction scores may suffer changes in their diagnostic accuracy. The aim of this study was to test the 30-day mortality predictive validity of the 4C and SEIMC scores during the sixth wave of the pandemic and to compare them with those of validation studies. This was a longitudinal retrospective observational study. COVID-19 patients who were admitted to the Emergency Department of a Spanish hospital from December 15, 2021, to January 31, 2022, were selected. A side-by-side comparison with the pivotal validation studies was subsequently performed. The main measures were 30-day mortality and the 4C and SEIMC scores. A total of 27,614 patients were considered in the study, including 22,361 from the 4C, 4,627 from the SEIMC and 626 from our hospital. The 30-day mortality rate was significantly lower than that reported in the validation studies. The AUCs were 0.931 (95% CI: 0.90–0.95) for 4C and 0.903 (95% CI: 086–0.93) for SEIMC, which were significantly greater than those obtained in the first wave. Despite the changes that have occurred during the coronavirus disease 2019 (COVID-19) pandemic, with a reduction in lethality, scorecard systems are currently still useful tools for detecting patients with poor disease risk, with better prognostic capacity.