• Paul M E L van Dam, Noortje Zelis, van KuijkSander M JSMJDepartment of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Center, Maastricht, The Netherlands., Aimée E M J H Linkens, Renée A G Brüggemann, Bart Spaetgens, van der HorstIwan C CICCDepartment of Intensive Care Medicine, Maastricht University Medical Center, Maastricht, The Netherlands., and Patricia M Stassen.
• Department of Internal Medicine, Division of General Internal Medicine, Section Acute Medicine, Maastricht University Medical Center, Maastricht, The Netherlands.
• Ann. Med. 2021 Dec 1; 53 (1): 402409402-409.

IntroductionCoronavirus disease 2019 (COVID-19) has a high burden on the healthcare system. Prediction models may assist in triaging patients. We aimed to assess the value of several prediction models in COVID-19 patients in the emergency department (ED).MethodsIn this retrospective study, ED patients with COVID-19 were included. Prediction models were selected based on their feasibility. Primary outcome was 30-day mortality, secondary outcomes were 14-day mortality and a composite outcome of 30-day mortality and admission to medium care unit (MCU) or intensive care unit (ICU). The discriminatory performance of the prediction models was assessed using an area under the receiver operating characteristic curve (AUC).ResultsWe included 403 patients. Thirty-day mortality was 23.6%, 14-day mortality was 19.1%, 66 patients (16.4%) were admitted to ICU, 48 patients (11.9%) to MCU, and 152 patients (37.7%) met the composite endpoint. Eleven prediction models were included. The RISE UP score and 4 C mortality scores showed very good discriminatory performance for 30-day mortality (AUC 0.83 and 0.84, 95% CI 0.79-0.88 for both), significantly higher than that of the other models.ConclusionThe RISE UP score and 4 C mortality score can be used to recognise patients at high risk for poor outcome and may assist in guiding decision-making and allocating resources.

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