COVID Outcome Prediction in the Emergency Department (COPE)

Background and aim: The COVID-19 pandemic is putting extraordinary pressure on emergency departments (EDs). To support decision making about hospital admission, we aimed to develop a simple and valid model for predicting mortality and need for admission to an intensive care unit (ICU) in suspected-COVID-19 patients presenting at the ED. Methods: For model development, we included patients that presented at the ED and were admitted to 4 large Dutch hospitals with suspected COVID-19 between March and August 2020, the first wave of the pandemic in the Netherlands. Based on prior literature we included patient characteristics, vital parameters and blood test values, all measured at ED admission, as potential predictors. Logistic regression analyses with post-hoc uniform shrinkage was used to obtain predicted probabilities of in-hospital death and of being admitted to the ICU, both within 28 days after admission. Model performance (AUC; calibration plots, intercepts and slopes) was assessed with temporal validation in patients who presented between September and December 2020 (second wave). We used multiple imputation to account for missing predictor values. Results: The development data included 5,831 patients who presented at the ED and were hospitalized, of whom 629 (10.8%) died and 5,070 (86.9%) were discharged within 28 days after admission. A simple model -- named COVID Outcome Prediction in the Emergency Department (COPE) -- with linear age and logarithmic transforms of respiratory rate, CRP, LDH, albumin and urea captured most of the ability to predict death within 28 days. Patients who were admitted in the first month of the pandemic had substantially increased risk of death (odds ratio 1.99; 95% CI 1.61-2.47). COPE was well-calibrated and showed good discrimination for predicting death in 3,252 patients of the second wave (AUC in 4 hospitals: 0.82; 0.82; 0.79; 0.83). COPE was also able to identify patients at high risk of needing IC in second wave patients below the age of 70 (AUC 0.84; 0.81), but overestimated ICU admission for low-risk patients. The models are implemented as a web-based application. Conclusion: COPE is a simple tool that is well able to predict mortality and ICU admission for patients who present to the ED with suspected COVID-19 and may help to inform patients and doctors when deciding on hospital admission.