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Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores
AIMS: To identify the most accurate early warning score (EWS) for predicting an adverse outcome in COVID-19 patients admitted to the emergency department (ED). METHODS: In adult consecutive patients admitted (March 1-April 15, 2020) to the ED of a major referral centre for COVID-19, we retrospective...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7480278/ https://www.ncbi.nlm.nih.gov/pubmed/32918985 http://dx.doi.org/10.1016/j.resuscitation.2020.08.124 |
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author | Covino, Marcello Sandroni, Claudio Santoro, Michele Sabia, Luca Simeoni, Benedetta Bocci, Maria Grazia Ojetti, Veronica Candelli, Marcello Antonelli, Massimo Gasbarrini, Antonio Franceschi, Francesco |
author_facet | Covino, Marcello Sandroni, Claudio Santoro, Michele Sabia, Luca Simeoni, Benedetta Bocci, Maria Grazia Ojetti, Veronica Candelli, Marcello Antonelli, Massimo Gasbarrini, Antonio Franceschi, Francesco |
author_sort | Covino, Marcello |
collection | PubMed |
description | AIMS: To identify the most accurate early warning score (EWS) for predicting an adverse outcome in COVID-19 patients admitted to the emergency department (ED). METHODS: In adult consecutive patients admitted (March 1-April 15, 2020) to the ED of a major referral centre for COVID-19, we retrospectively calculated NEWS, NEWS2, NEWS-C, MEWS, qSOFA, and REMS from physiological variables measured on arrival. Sensitivity, specificity, positive (PPV) and negative predictive value (NPV), and the area under the receiver operating characteristic (AUROC) curve of each EWS for predicting admission to the intensive care unit (ICU) and death at 48 h and 7 days were calculated. RESULTS: We included 334 patients (119 [35.6%] females, median age 66 [54-78] years). At 7 days, the rates of ICU admission and death were 56/334 (17%) and 26/334 (7.8%), respectively. NEWS was the most accurate predictor of ICU admission within 7 days (AUROC 0.783 [95% CI, 0.735-0.826]; sensitivity 71.4 [57.8-82.7]%; NPV 93.1 [89.8-95.3]%), while REMS was the most accurate predictor of death within 7 days (AUROC 0.823 [0.778–0.863]; sensitivity 96.1 [80.4-99.9]%; NPV 99.4[96.2–99.9]%). Similar results were observed for ICU admission and death at 48 h. NEWS and REMS were as accurate as the triage system used in our ED. MEWS and qSOFA had the lowest overall accuracy for both outcomes. CONCLUSION: In our single-centre cohort of COVID-19 patients, NEWS and REMS measured on ED arrival were the most sensitive predictors of 7-day ICU admission or death. EWS could be useful to identify patients with low risk of clinical deterioration. |
format | Online Article Text |
id | pubmed-7480278 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74802782020-09-09 Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores Covino, Marcello Sandroni, Claudio Santoro, Michele Sabia, Luca Simeoni, Benedetta Bocci, Maria Grazia Ojetti, Veronica Candelli, Marcello Antonelli, Massimo Gasbarrini, Antonio Franceschi, Francesco Resuscitation Clinical Paper AIMS: To identify the most accurate early warning score (EWS) for predicting an adverse outcome in COVID-19 patients admitted to the emergency department (ED). METHODS: In adult consecutive patients admitted (March 1-April 15, 2020) to the ED of a major referral centre for COVID-19, we retrospectively calculated NEWS, NEWS2, NEWS-C, MEWS, qSOFA, and REMS from physiological variables measured on arrival. Sensitivity, specificity, positive (PPV) and negative predictive value (NPV), and the area under the receiver operating characteristic (AUROC) curve of each EWS for predicting admission to the intensive care unit (ICU) and death at 48 h and 7 days were calculated. RESULTS: We included 334 patients (119 [35.6%] females, median age 66 [54-78] years). At 7 days, the rates of ICU admission and death were 56/334 (17%) and 26/334 (7.8%), respectively. NEWS was the most accurate predictor of ICU admission within 7 days (AUROC 0.783 [95% CI, 0.735-0.826]; sensitivity 71.4 [57.8-82.7]%; NPV 93.1 [89.8-95.3]%), while REMS was the most accurate predictor of death within 7 days (AUROC 0.823 [0.778–0.863]; sensitivity 96.1 [80.4-99.9]%; NPV 99.4[96.2–99.9]%). Similar results were observed for ICU admission and death at 48 h. NEWS and REMS were as accurate as the triage system used in our ED. MEWS and qSOFA had the lowest overall accuracy for both outcomes. CONCLUSION: In our single-centre cohort of COVID-19 patients, NEWS and REMS measured on ED arrival were the most sensitive predictors of 7-day ICU admission or death. EWS could be useful to identify patients with low risk of clinical deterioration. Elsevier B.V. 2020-11 2020-09-09 /pmc/articles/PMC7480278/ /pubmed/32918985 http://dx.doi.org/10.1016/j.resuscitation.2020.08.124 Text en © 2020 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Clinical Paper Covino, Marcello Sandroni, Claudio Santoro, Michele Sabia, Luca Simeoni, Benedetta Bocci, Maria Grazia Ojetti, Veronica Candelli, Marcello Antonelli, Massimo Gasbarrini, Antonio Franceschi, Francesco Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores |
title | Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores |
title_full | Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores |
title_fullStr | Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores |
title_full_unstemmed | Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores |
title_short | Predicting intensive care unit admission and death for COVID-19 patients in the emergency department using early warning scores |
title_sort | predicting intensive care unit admission and death for covid-19 patients in the emergency department using early warning scores |
topic | Clinical Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7480278/ https://www.ncbi.nlm.nih.gov/pubmed/32918985 http://dx.doi.org/10.1016/j.resuscitation.2020.08.124 |
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