COVID outcome prediction in the emergency department (COPE): using retrospective Dutch hospital data to develop simple and valid models for predicting mortality and need for intensive care unit admission in patients who present at the emergency department with suspected COVID-19

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, Hilde R. H. de Geus, Rozemarijn L. Van Bruchem-Visser, Jelle R. Miedema, Annelies Verbon, Els van Nood, David M. Kent, Stephanie C. E. Schuit, Hester Lingsma

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Objectives Develop 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. Design Retrospective. Setting Secondary care in four large Dutch hospitals. Participants Patients 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 measures We 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. Results Of 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)). Conclusions COPE 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.
Original languageEnglish
Article numbere051468
Number of pages14
JournalBMJ Open
Volume11
Issue number9
DOIs
Publication statusPublished - 1 Sept 2021

Keywords

  • COVID-19
  • public health
  • accident & emergency medicine
  • epidemiology
  • INDIVIDUAL PROGNOSIS
  • DIAGNOSIS TRIPOD
  • RISK
  • EXPLANATION

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