• David van Klaveren, Alexandros Rekkas, Jelmer Alsma, Rob J C G Verdonschot, Dick T J J Koning, Marlijn J A Kamps, Tom Dormans, Robert Stassen, Sebastiaan Weijer, Klaas-Sierk Arnold, Benjamin Tomlow, de GeusHilde R HHRHDepartment of Intensive Care, Erasmus MC, Rotterdam, The Netherlands., Rozemarijn L van Bruchem-Visser, Jelle R Miedema, Annelies Verbon, Els van Nood, David M Kent, SchuitStephanie C ESCEExecutive Board, UMCG, Groningen, The Netherlands., and Hester Lingsma.
• Department of Public Health, Erasmus MC, Rotterdam, The Netherlands d.vanklaveren@erasmusmc.nl.
• BMJ Open. 2021 Sep 16; 11 (9): e051468.

ObjectivesDevelop simple and valid models for predicting mortality and need for intensive care unit (ICU) admission in patients who present at the emergency department (ED) with suspected COVID-19.DesignRetrospective.SettingSecondary care in four large Dutch hospitals.ParticipantsPatients who presented at the ED and were admitted to hospital with suspected COVID-19. We used 5831 first-wave patients who presented between March and August 2020 for model development and 3252 second-wave patients who presented between September and December 2020 for model validation.Outcome MeasuresWe developed separate logistic regression models for in-hospital death and for need for ICU admission, both within 28 days after hospital admission. Based on prior literature, we considered quickly and objectively obtainable patient characteristics, vital parameters and blood test values as predictors. We assessed model performance by the area under the receiver operating characteristic curve (AUC) and by calibration plots.ResultsOf 5831 first-wave patients, 629 (10.8%) died within 28 days after admission. ICU admission was fully recorded for 2633 first-wave patients in 2 hospitals, with 214 (8.1%) ICU admissions within 28 days. A simple model-COVID outcome prediction in the emergency department (COPE)-with age, respiratory rate, C reactive protein, lactate dehydrogenase, albumin and urea captured most of the ability to predict death. COPE was well calibrated and showed good discrimination for mortality in second-wave patients (AUC in four hospitals: 0.82 (95% CI 0.78 to 0.86); 0.82 (95% CI 0.74 to 0.90); 0.79 (95% CI 0.70 to 0.88); 0.83 (95% CI 0.79 to 0.86)). COPE was also able to identify patients at high risk of needing ICU admission in second-wave patients (AUC in two hospitals: 0.84 (95% CI 0.78 to 0.90); 0.81 (95% CI 0.66 to 0.95)).ConclusionsCOPE is a simple tool that is well able to predict mortality and need for ICU admission in patients who present to the ED with suspected COVID-19 and may help patients and doctors in decision making.© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

12 keywords...

hide…