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Risk factors for the critical illness in SARS-CoV-2 infection: a multicenter retrospective cohort study

BACKGROUND: Prior studies reported that 5 ~ 32% COVID-19 patients were critically ill, a situation that poses great challenge for the management of the patients and ICU resources. We aim to identify independent risk factors to serve as prediction markers for critical illness of SARS-CoV-2 infection....

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Autores principales: Cheng, Sijing, Wu, Dingfeng, Li, Jie, Zou, Yifeng, Wan, Yunle, Shen, Lihan, Zhu, Lixin, Shi, Mang, Hou, Linlin, Xu, Tao, Jiao, Na, Li, Yichen, Huang, Yibo, Tang, Zhipeng, Xu, Mingwei, Jiang, Shusong, Li, Maokun, Yan, Guangjun, Lan, Ping, Zhu, Ruixin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576549/
https://www.ncbi.nlm.nih.gov/pubmed/33087114
http://dx.doi.org/10.1186/s12931-020-01492-z
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author Cheng, Sijing
Wu, Dingfeng
Li, Jie
Zou, Yifeng
Wan, Yunle
Shen, Lihan
Zhu, Lixin
Shi, Mang
Hou, Linlin
Xu, Tao
Jiao, Na
Li, Yichen
Huang, Yibo
Tang, Zhipeng
Xu, Mingwei
Jiang, Shusong
Li, Maokun
Yan, Guangjun
Lan, Ping
Zhu, Ruixin
author_facet Cheng, Sijing
Wu, Dingfeng
Li, Jie
Zou, Yifeng
Wan, Yunle
Shen, Lihan
Zhu, Lixin
Shi, Mang
Hou, Linlin
Xu, Tao
Jiao, Na
Li, Yichen
Huang, Yibo
Tang, Zhipeng
Xu, Mingwei
Jiang, Shusong
Li, Maokun
Yan, Guangjun
Lan, Ping
Zhu, Ruixin
author_sort Cheng, Sijing
collection PubMed
description BACKGROUND: Prior studies reported that 5 ~ 32% COVID-19 patients were critically ill, a situation that poses great challenge for the management of the patients and ICU resources. We aim to identify independent risk factors to serve as prediction markers for critical illness of SARS-CoV-2 infection. METHODS: Fifty-two critical and 200 non-critical SARS-CoV-2 nucleic acid positive patients hospitalized in 15 hospitals outside Wuhan from January 19 to March 6, 2020 were enrolled in this study. Multivariable logistic regression and LASSO logistic regression were performed to identify independent risk factors for critical illness. RESULTS: Age older than 60 years, dyspnea, respiratory rate > 24 breaths per min, leukocytosis > 9.5 × 10(9)/L, neutrophilia > 6.3 × 10(9)/L, lymphopenia < 1.1 × 10(9)/L, neutrophil-to-lymphocyte ratio > 3.53, fibrinogen > 4 g/L, d-dimer > 0.55 μg/mL, blood urea nitrogen > 7.1 mM, elevated aspartate transaminase, elevated alanine aminotransferase, total bilirubin > 21 μM, and Sequential Organ Failure Assessment (SOFA) score ≥ 2 were identified as risk factors for critical illness. LASSO logistic regression identified the best combination of risk factors as SOFA score, age, dyspnea, and leukocytosis. The Area Under the Receiver-Operator Curve values for the risk factors in predicting critical illness were 0.921 for SOFA score, 0.776 for age, 0.764 for dyspnea, 0.658 for leukocytosis, and 0.960 for the combination of the four risk factors. CONCLUSIONS: Our findings advocate the use of risk factors SOFA score ≥ 2, age > 60, dyspnea and leukocytosis > 9.5 × 10(9)/L on admission, alone or in combination, to determine the optimal management of the patients and health care resources.
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spelling pubmed-75765492020-10-21 Risk factors for the critical illness in SARS-CoV-2 infection: a multicenter retrospective cohort study Cheng, Sijing Wu, Dingfeng Li, Jie Zou, Yifeng Wan, Yunle Shen, Lihan Zhu, Lixin Shi, Mang Hou, Linlin Xu, Tao Jiao, Na Li, Yichen Huang, Yibo Tang, Zhipeng Xu, Mingwei Jiang, Shusong Li, Maokun Yan, Guangjun Lan, Ping Zhu, Ruixin Respir Res Research BACKGROUND: Prior studies reported that 5 ~ 32% COVID-19 patients were critically ill, a situation that poses great challenge for the management of the patients and ICU resources. We aim to identify independent risk factors to serve as prediction markers for critical illness of SARS-CoV-2 infection. METHODS: Fifty-two critical and 200 non-critical SARS-CoV-2 nucleic acid positive patients hospitalized in 15 hospitals outside Wuhan from January 19 to March 6, 2020 were enrolled in this study. Multivariable logistic regression and LASSO logistic regression were performed to identify independent risk factors for critical illness. RESULTS: Age older than 60 years, dyspnea, respiratory rate > 24 breaths per min, leukocytosis > 9.5 × 10(9)/L, neutrophilia > 6.3 × 10(9)/L, lymphopenia < 1.1 × 10(9)/L, neutrophil-to-lymphocyte ratio > 3.53, fibrinogen > 4 g/L, d-dimer > 0.55 μg/mL, blood urea nitrogen > 7.1 mM, elevated aspartate transaminase, elevated alanine aminotransferase, total bilirubin > 21 μM, and Sequential Organ Failure Assessment (SOFA) score ≥ 2 were identified as risk factors for critical illness. LASSO logistic regression identified the best combination of risk factors as SOFA score, age, dyspnea, and leukocytosis. The Area Under the Receiver-Operator Curve values for the risk factors in predicting critical illness were 0.921 for SOFA score, 0.776 for age, 0.764 for dyspnea, 0.658 for leukocytosis, and 0.960 for the combination of the four risk factors. CONCLUSIONS: Our findings advocate the use of risk factors SOFA score ≥ 2, age > 60, dyspnea and leukocytosis > 9.5 × 10(9)/L on admission, alone or in combination, to determine the optimal management of the patients and health care resources. BioMed Central 2020-10-21 2020 /pmc/articles/PMC7576549/ /pubmed/33087114 http://dx.doi.org/10.1186/s12931-020-01492-z Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Cheng, Sijing
Wu, Dingfeng
Li, Jie
Zou, Yifeng
Wan, Yunle
Shen, Lihan
Zhu, Lixin
Shi, Mang
Hou, Linlin
Xu, Tao
Jiao, Na
Li, Yichen
Huang, Yibo
Tang, Zhipeng
Xu, Mingwei
Jiang, Shusong
Li, Maokun
Yan, Guangjun
Lan, Ping
Zhu, Ruixin
Risk factors for the critical illness in SARS-CoV-2 infection: a multicenter retrospective cohort study
title Risk factors for the critical illness in SARS-CoV-2 infection: a multicenter retrospective cohort study
title_full Risk factors for the critical illness in SARS-CoV-2 infection: a multicenter retrospective cohort study
title_fullStr Risk factors for the critical illness in SARS-CoV-2 infection: a multicenter retrospective cohort study
title_full_unstemmed Risk factors for the critical illness in SARS-CoV-2 infection: a multicenter retrospective cohort study
title_short Risk factors for the critical illness in SARS-CoV-2 infection: a multicenter retrospective cohort study
title_sort risk factors for the critical illness in sars-cov-2 infection: a multicenter retrospective cohort study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576549/
https://www.ncbi.nlm.nih.gov/pubmed/33087114
http://dx.doi.org/10.1186/s12931-020-01492-z
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