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
PY - 2021/9/1
Y1 - 2021/9/1
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
SN - 2044-6055
VL - 11
JO - BMJ Open
JF - BMJ Open
IS - 9
M1 - e051468
ER -