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
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 pr...
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BMJ Publishing Group
2021-09-01
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| author | Annelies Verbon Jelmer Alsma Hester Lingsma David M Kent David van Klaveren Rozemarijn L van Bruchem-Visser Tom Dormans Stephanie C E Schuit Alexandros Rekkas Rob J C G Verdonschot Dick T J J Koning Marlijn J A Kamps Robert Stassen Sebastiaan Weijer Klaas-Sierk Arnold Benjamin Tomlow Hilde R H de Geus Jelle R Miedema Els van Nood |
| author_facet | Annelies Verbon Jelmer Alsma Hester Lingsma David M Kent David van Klaveren Rozemarijn L van Bruchem-Visser Tom Dormans Stephanie C E Schuit Alexandros Rekkas Rob J C G Verdonschot Dick T J J Koning Marlijn J A Kamps Robert Stassen Sebastiaan Weijer Klaas-Sierk Arnold Benjamin Tomlow Hilde R H de Geus Jelle R Miedema Els van Nood |
| author_sort | Annelies Verbon |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9d70e869cce4427698f00fbaa5ce28fb |
| institution | OA Journals |
| issn | 2044-6055 |
| language | English |
| publishDate | 2021-09-01 |
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| series | BMJ Open |
| spelling | doaj-art-9d70e869cce4427698f00fbaa5ce28fb2025-08-20T02:18:35ZengBMJ Publishing GroupBMJ Open2044-60552021-09-0111910.1136/bmjopen-2021-051468COVID 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-19Annelies Verbon0Jelmer Alsma1Hester Lingsma2David M Kent3David van Klaveren4Rozemarijn L van Bruchem-Visser5Tom Dormans6Stephanie C E Schuit7Alexandros Rekkas8Rob J C G Verdonschot9Dick T J J Koning10Marlijn J A Kamps11Robert Stassen12Sebastiaan Weijer13Klaas-Sierk Arnold14Benjamin Tomlow15Hilde R H de Geus16Jelle R Miedema17Els van Nood18Department of Medical Microbiology and Infectious Diseases, Erasmus MC, Rotterdam, NetherlandsRotterdam Marathon Study Group, Rotterdam, The NetherlandsDepartment of Public Health, Erasmus MC, Rotterdam, Netherlandsprofessor of medicinePredictive Analytics and Comparative Effectiveness Center, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts, USADepartment of Internal Medicine, Erasmus MC, Rotterdam, The NetherlandsVascular Medicine, Amsterdam University Medical Centers, Amsterdam, NetherlandsExecutive Board, UMCG, Groningen, The NetherlandsDepartment of Medical Informatics, Erasmus MC, Rotterdam, The NetherlandsEmergency Department, Erasmus MC, Rotterdam, The NetherlandsDepartment of Intensive Care, Catharina Hospital, Eindhoven, The NetherlandsDepartment of Intensive Care, Catharina Hospital, Eindhoven, The NetherlandsDepartment of Traumatology, Maastricht University Medical Centre+, Maastricht, The NetherlandsDepartment of Internal Medicine, Antonius Hospital Sneek, Sneek, The NetherlandsDepartment of Intensive Care, Antonius Hospital Sneek, Sneek, The NetherlandsDepartment of Pulmonary Medicine, Isala Hospitals, Zwolle, The NetherlandsDepartment of Intensive Care, Erasmus MC, Rotterdam, The NetherlandsDepartment of Pulmonary Medicine, Erasmus MC, Rotterdam, The NetherlandsDepartment of Internal Medicine, Department of Medical Microbiology and Infectious Diseases, Erasmus MC, Rotterdam, The NetherlandsObjectives 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.https://bmjopen.bmj.com/content/11/9/e051468.full |
| spellingShingle | Annelies Verbon Jelmer Alsma Hester Lingsma David M Kent David van Klaveren Rozemarijn L van Bruchem-Visser Tom Dormans Stephanie C E Schuit Alexandros Rekkas Rob J C G Verdonschot Dick T J J Koning Marlijn J A Kamps Robert Stassen Sebastiaan Weijer Klaas-Sierk Arnold Benjamin Tomlow Hilde R H de Geus Jelle R Miedema Els van Nood 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 BMJ Open |
| title | 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| url | https://bmjopen.bmj.com/content/11/9/e051468.full |
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