TY - JOUR
T1 - COVID outcome prediction in the emergency department (COPE)
T2 - 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
AU - van Klaveren, David
AU - Rekkas, Alexandros
AU - Alsma, Jelmer
AU - Verdonschot, Rob J. C. G.
AU - Koning, Dick T. J. J.
AU - Kamps, Marlijn J. A.
AU - Dormans, Tom
AU - Stassen, Robert
AU - Weijer, Sebastiaan
AU - Arnold, Klaas-Sierk
AU - Tomlow, Benjamin
AU - de Geus, Hilde R. H.
AU - Van Bruchem-Visser, Rozemarijn L.
AU - Miedema, Jelle R.
AU - Verbon, Annelies
AU - van Nood, Els
AU - Kent, David M.
AU - Schuit, Stephanie C. E.
AU - Lingsma, Hester
N1 - © 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.
PY - 2021/9/16
Y1 - 2021/9/16
N2 - 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.
AB - 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.
KW - COVID-19
KW - public health
KW - accident & emergency medicine
KW - epidemiology
KW - INDIVIDUAL PROGNOSIS
KW - DIAGNOSIS TRIPOD
KW - RISK
KW - EXPLANATION
U2 - 10.1136/bmjopen-2021-051468
DO - 10.1136/bmjopen-2021-051468
M3 - Article
C2 - 34531219
SN - 2044-6055
VL - 11
JO - BMJ Open
JF - BMJ Open
IS - 9
M1 - 051468
ER -