Performance of prediction models for short-term outcome in COVID-19 patients in the emergency department: a retrospective study
AbstractIntroduction Coronavirus disease 2019 (COVID-19) has a high burden on the healthcare system. Prediction models may assist in triaging patients. We aimed to assess the value of several prediction models in COVID-19 patients in the emergency department (ED).Methods In this retrospective study,...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2021-01-01
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| Series: | Annals of Medicine |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/07853890.2021.1891453 |
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| author | Paul M. E. L. van Dam Noortje Zelis Sander M. J. van Kuijk Aimée E. M. J. H. Linkens Renée A. G. Brüggemann Bart Spaetgens Iwan C. C. van der Horst Patricia M. Stassen |
| author_facet | Paul M. E. L. van Dam Noortje Zelis Sander M. J. van Kuijk Aimée E. M. J. H. Linkens Renée A. G. Brüggemann Bart Spaetgens Iwan C. C. van der Horst Patricia M. Stassen |
| author_sort | Paul M. E. L. van Dam |
| collection | DOAJ |
| description | AbstractIntroduction Coronavirus disease 2019 (COVID-19) has a high burden on the healthcare system. Prediction models may assist in triaging patients. We aimed to assess the value of several prediction models in COVID-19 patients in the emergency department (ED).Methods In this retrospective study, ED patients with COVID-19 were included. Prediction models were selected based on their feasibility. Primary outcome was 30-day mortality, secondary outcomes were 14-day mortality and a composite outcome of 30-day mortality and admission to medium care unit (MCU) or intensive care unit (ICU). The discriminatory performance of the prediction models was assessed using an area under the receiver operating characteristic curve (AUC).Results We included 403 patients. Thirty-day mortality was 23.6%, 14-day mortality was 19.1%, 66 patients (16.4%) were admitted to ICU, 48 patients (11.9%) to MCU, and 152 patients (37.7%) met the composite endpoint. Eleven prediction models were included. The RISE UP score and 4 C mortality scores showed very good discriminatory performance for 30-day mortality (AUC 0.83 and 0.84, 95% CI 0.79-0.88 for both), significantly higher than that of the other models.Conclusion The RISE UP score and 4 C mortality score can be used to recognise patients at high risk for poor outcome and may assist in guiding decision-making and allocating resources. |
| first_indexed | 2024-03-08T21:58:03Z |
| format | Article |
| id | doaj.art-6f51d72d9cf0449aa4e966e06199f6b0 |
| institution | Directory Open Access Journal |
| issn | 0785-3890 1365-2060 |
| language | English |
| last_indexed | 2024-03-08T21:58:03Z |
| publishDate | 2021-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Annals of Medicine |
| spelling | doaj.art-6f51d72d9cf0449aa4e966e06199f6b02023-12-19T16:46:26ZengTaylor & Francis GroupAnnals of Medicine0785-38901365-20602021-01-0153140240910.1080/07853890.2021.1891453Performance of prediction models for short-term outcome in COVID-19 patients in the emergency department: a retrospective studyPaul M. E. L. van Dam0Noortje Zelis1Sander M. J. van Kuijk2Aimée E. M. J. H. Linkens3Renée A. G. Brüggemann4Bart Spaetgens5Iwan C. C. van der Horst6Patricia M. Stassen7Department of Internal Medicine, Division of General Internal Medicine, Section Acute Medicine, Maastricht University Medical Center, Maastricht, The NetherlandsDepartment of Internal Medicine, Division of General Internal Medicine, Section Acute Medicine, Maastricht University Medical Center, Maastricht, The NetherlandsDepartment of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Center, Maastricht, The NetherlandsDepartment of Internal Medicine, Division of General Internal Medicine, Section Geriatric Medicine, Maastricht University Medical Center, Maastricht, The NetherlandsDepartment of Internal Medicine, Division of General Internal Medicine, Section Geriatric Medicine, Maastricht University Medical Center, Maastricht, The NetherlandsDepartment of Internal Medicine, Division of General Internal Medicine, Section Geriatric Medicine, Maastricht University Medical Center, Maastricht, The NetherlandsDepartment of Intensive Care Medicine, Maastricht University Medical Center, Maastricht, The NetherlandsDepartment of Internal Medicine, Division of General Internal Medicine, Section Acute Medicine, Maastricht University Medical Center, Maastricht, The NetherlandsAbstractIntroduction Coronavirus disease 2019 (COVID-19) has a high burden on the healthcare system. Prediction models may assist in triaging patients. We aimed to assess the value of several prediction models in COVID-19 patients in the emergency department (ED).Methods In this retrospective study, ED patients with COVID-19 were included. Prediction models were selected based on their feasibility. Primary outcome was 30-day mortality, secondary outcomes were 14-day mortality and a composite outcome of 30-day mortality and admission to medium care unit (MCU) or intensive care unit (ICU). The discriminatory performance of the prediction models was assessed using an area under the receiver operating characteristic curve (AUC).Results We included 403 patients. Thirty-day mortality was 23.6%, 14-day mortality was 19.1%, 66 patients (16.4%) were admitted to ICU, 48 patients (11.9%) to MCU, and 152 patients (37.7%) met the composite endpoint. Eleven prediction models were included. The RISE UP score and 4 C mortality scores showed very good discriminatory performance for 30-day mortality (AUC 0.83 and 0.84, 95% CI 0.79-0.88 for both), significantly higher than that of the other models.Conclusion The RISE UP score and 4 C mortality score can be used to recognise patients at high risk for poor outcome and may assist in guiding decision-making and allocating resources.https://www.tandfonline.com/doi/10.1080/07853890.2021.1891453COVID-19predictionprognosismortalityemergency department |
| spellingShingle | Paul M. E. L. van Dam Noortje Zelis Sander M. J. van Kuijk Aimée E. M. J. H. Linkens Renée A. G. Brüggemann Bart Spaetgens Iwan C. C. van der Horst Patricia M. Stassen Performance of prediction models for short-term outcome in COVID-19 patients in the emergency department: a retrospective study Annals of Medicine COVID-19 prediction prognosis mortality emergency department |
| title | Performance of prediction models for short-term outcome in COVID-19 patients in the emergency department: a retrospective study |
| title_full | Performance of prediction models for short-term outcome in COVID-19 patients in the emergency department: a retrospective study |
| title_fullStr | Performance of prediction models for short-term outcome in COVID-19 patients in the emergency department: a retrospective study |
| title_full_unstemmed | Performance of prediction models for short-term outcome in COVID-19 patients in the emergency department: a retrospective study |
| title_short | Performance of prediction models for short-term outcome in COVID-19 patients in the emergency department: a retrospective study |
| title_sort | performance of prediction models for short term outcome in covid 19 patients in the emergency department a retrospective study |
| topic | COVID-19 prediction prognosis mortality emergency department |
| url | https://www.tandfonline.com/doi/10.1080/07853890.2021.1891453 |
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