Cargando…

Predicting severe COVID-19 in the Emergency Department

BACKGROUND: COVID-19 may lead to severe disease, requiring intensive care treatment and challenging the capacity of health care systems. The aim of this study was to compare the ability of commonly used scoring systems for sepsis and pneumonia to predict severe COVID-19 in the emergency department....

Descripción completa

Detalles Bibliográficos
Autores principales: Holten, Aleksander Rygh, Nore, Kristin Grotle, Tveiten, Caroline Emilie Van Woensel Kooy, Olasveengen, Theresa Mariero, Tonby, Kristian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577659/
https://www.ncbi.nlm.nih.gov/pubmed/33403367
http://dx.doi.org/10.1016/j.resplu.2020.100042
_version_ 1783598219372003328
author Holten, Aleksander Rygh
Nore, Kristin Grotle
Tveiten, Caroline Emilie Van Woensel Kooy
Olasveengen, Theresa Mariero
Tonby, Kristian
author_facet Holten, Aleksander Rygh
Nore, Kristin Grotle
Tveiten, Caroline Emilie Van Woensel Kooy
Olasveengen, Theresa Mariero
Tonby, Kristian
author_sort Holten, Aleksander Rygh
collection PubMed
description BACKGROUND: COVID-19 may lead to severe disease, requiring intensive care treatment and challenging the capacity of health care systems. The aim of this study was to compare the ability of commonly used scoring systems for sepsis and pneumonia to predict severe COVID-19 in the emergency department. METHODS: Prospective, observational, single centre study in a secondary/tertiary care hospital in Oslo, Norway. Patients were assessed upon hospital admission using the following scoring systems; quick Sequential Failure Assessment (qSOFA), Systemic Inflammatory Response Syndrome criteria (SIRS), National Early Warning Score 2 (NEWS2), CURB-65 and Pneumonia Severity index (PSI). The ratio of arterial oxygen tension to inspiratory oxygen fraction (P/F-ratio) was also calculated. The area under the receiver operating characteristics curve (AUROC) for each scoring system was calculated, along with sensitivity and specificity for the most commonly used cut-offs. Severe disease was defined as death or treatment in ICU within 14 days. RESULTS: 38 of 175 study participants developed severe disease, 13 (7%) died and 29 (17%) had a stay at an intensive care unit (ICU). NEWS2 displayed an AUROC of 0.80 (95% confidence interval 0.72−0.88), CURB-65 0.75 (0.65−0.84), PSI 0.75 (0.65−0.84), SIRS 0.70 (0.61–0.80) and qSOFA 0.70 (0.61−0.79). NEWS2 was significantly better than SIRS and qSOFA in predicating severe disease, and with a cut-off of5 points, had a sensitivity and specificity of 82% and 60%, respectively. CONCLUSION: NEWS2 predicted severe COVID-19 disease more accurately than SIRS and qSOFA, but not significantly better than CURB65 and PSI. NEWS2 may be a useful screening tool in evaluating COVID-19 patients during hospital admission. TRIAL REGISTRATION: : ClinicalTrials.gov Identifier: NCT04345536. (https://clinicaltrials.gov/ct2/show/NCT04345536).
format Online
Article
Text
id pubmed-7577659
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-75776592020-10-22 Predicting severe COVID-19 in the Emergency Department Holten, Aleksander Rygh Nore, Kristin Grotle Tveiten, Caroline Emilie Van Woensel Kooy Olasveengen, Theresa Mariero Tonby, Kristian Resusc Plus Clinical Paper BACKGROUND: COVID-19 may lead to severe disease, requiring intensive care treatment and challenging the capacity of health care systems. The aim of this study was to compare the ability of commonly used scoring systems for sepsis and pneumonia to predict severe COVID-19 in the emergency department. METHODS: Prospective, observational, single centre study in a secondary/tertiary care hospital in Oslo, Norway. Patients were assessed upon hospital admission using the following scoring systems; quick Sequential Failure Assessment (qSOFA), Systemic Inflammatory Response Syndrome criteria (SIRS), National Early Warning Score 2 (NEWS2), CURB-65 and Pneumonia Severity index (PSI). The ratio of arterial oxygen tension to inspiratory oxygen fraction (P/F-ratio) was also calculated. The area under the receiver operating characteristics curve (AUROC) for each scoring system was calculated, along with sensitivity and specificity for the most commonly used cut-offs. Severe disease was defined as death or treatment in ICU within 14 days. RESULTS: 38 of 175 study participants developed severe disease, 13 (7%) died and 29 (17%) had a stay at an intensive care unit (ICU). NEWS2 displayed an AUROC of 0.80 (95% confidence interval 0.72−0.88), CURB-65 0.75 (0.65−0.84), PSI 0.75 (0.65−0.84), SIRS 0.70 (0.61–0.80) and qSOFA 0.70 (0.61−0.79). NEWS2 was significantly better than SIRS and qSOFA in predicating severe disease, and with a cut-off of5 points, had a sensitivity and specificity of 82% and 60%, respectively. CONCLUSION: NEWS2 predicted severe COVID-19 disease more accurately than SIRS and qSOFA, but not significantly better than CURB65 and PSI. NEWS2 may be a useful screening tool in evaluating COVID-19 patients during hospital admission. TRIAL REGISTRATION: : ClinicalTrials.gov Identifier: NCT04345536. (https://clinicaltrials.gov/ct2/show/NCT04345536). Elsevier 2020-10-21 /pmc/articles/PMC7577659/ /pubmed/33403367 http://dx.doi.org/10.1016/j.resplu.2020.100042 Text en © 2020 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Clinical Paper
Holten, Aleksander Rygh
Nore, Kristin Grotle
Tveiten, Caroline Emilie Van Woensel Kooy
Olasveengen, Theresa Mariero
Tonby, Kristian
Predicting severe COVID-19 in the Emergency Department
title Predicting severe COVID-19 in the Emergency Department
title_full Predicting severe COVID-19 in the Emergency Department
title_fullStr Predicting severe COVID-19 in the Emergency Department
title_full_unstemmed Predicting severe COVID-19 in the Emergency Department
title_short Predicting severe COVID-19 in the Emergency Department
title_sort predicting severe covid-19 in the emergency department
topic Clinical Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577659/
https://www.ncbi.nlm.nih.gov/pubmed/33403367
http://dx.doi.org/10.1016/j.resplu.2020.100042
work_keys_str_mv AT holtenaleksanderrygh predictingseverecovid19intheemergencydepartment
AT norekristingrotle predictingseverecovid19intheemergencydepartment
AT tveitencarolineemilievanwoenselkooy predictingseverecovid19intheemergencydepartment
AT olasveengentheresamariero predictingseverecovid19intheemergencydepartment
AT tonbykristian predictingseverecovid19intheemergencydepartment