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Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19
BACKGROUND: Patients with severe coronavirus disease 2019 (COVID-19) develop acute respiratory distress and multi-system organ failure and are associated with poor prognosis and high mortality. Thus, there is an urgent need to identify early diagnostic and prognostic biomarkers to determine the risk...
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/PMC7532789/ https://www.ncbi.nlm.nih.gov/pubmed/33045571 http://dx.doi.org/10.1016/j.intimp.2020.107065 |
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author | Xue, Guohui Gan, Xing Wu, Zhiqiang Xie, Dan Xiong, Yan Hua, Lin Zhou, Bing Zhou, Nanjin Xiang, Jie Li, Junming |
author_facet | Xue, Guohui Gan, Xing Wu, Zhiqiang Xie, Dan Xiong, Yan Hua, Lin Zhou, Bing Zhou, Nanjin Xiang, Jie Li, Junming |
author_sort | Xue, Guohui |
collection | PubMed |
description | BACKGROUND: Patients with severe coronavirus disease 2019 (COVID-19) develop acute respiratory distress and multi-system organ failure and are associated with poor prognosis and high mortality. Thus, there is an urgent need to identify early diagnostic and prognostic biomarkers to determine the risk of developing serious illness. METHODS: We retrospectively analyzed 114 patients with COVID-19 at the Jinyintan Hospital, Wuhan based on their clinical and laboratory data. Patients were categorized into severe and mild to moderate disease groups. We analyzed the potential of serological inflammation indicators in predicting the severity of COVID-19 in patients using univariate and multivariate logistic regression, receiver operating characteristic curves, and nomogram analysis. The Spearman method was used to understand the correlation between the serological biomarkers and duration of hospital stay. RESULTS: Patients with severe disease had reduced neutrophils and lymphocytes; severe coagulation dysfunction; altered content of biochemical factors (such as urea, lactate dehydrogenase); elevated high sensitivity C-reactive protein levels, neutrophil–lymphocyte, platelet-lymphocyte, and derived neutrophil–lymphocyte ratios, high sensitivity C-reactive protein-prealbumin ratio (HsCPAR), systemic immune-inflammation index, and high sensitivity C-reactive protein-albumin ratio (HsCAR); and low lymphocyte-monocyte ratio, prognostic nutritional index (PNI), and albumin-to-fibrinogen ratio. PNI, HsCAR, and HsCPAR correlated with the risk of severe disease. The nomogram combining the three parameters showed good discrimination with a C-index of 0.873 and reliable calibration. Moreover, HsCAR and HsCPAR correlated with duration of hospital stay. CONCLUSION: Taken together, PNI, HsCAR, and HsCPAR may serve as accurate biomarkers for the prediction of disease severity in patients with COVID-19 upon admission/hospitalization. |
format | Online Article Text |
id | pubmed-7532789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75327892020-10-05 Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19 Xue, Guohui Gan, Xing Wu, Zhiqiang Xie, Dan Xiong, Yan Hua, Lin Zhou, Bing Zhou, Nanjin Xiang, Jie Li, Junming Int Immunopharmacol Article BACKGROUND: Patients with severe coronavirus disease 2019 (COVID-19) develop acute respiratory distress and multi-system organ failure and are associated with poor prognosis and high mortality. Thus, there is an urgent need to identify early diagnostic and prognostic biomarkers to determine the risk of developing serious illness. METHODS: We retrospectively analyzed 114 patients with COVID-19 at the Jinyintan Hospital, Wuhan based on their clinical and laboratory data. Patients were categorized into severe and mild to moderate disease groups. We analyzed the potential of serological inflammation indicators in predicting the severity of COVID-19 in patients using univariate and multivariate logistic regression, receiver operating characteristic curves, and nomogram analysis. The Spearman method was used to understand the correlation between the serological biomarkers and duration of hospital stay. RESULTS: Patients with severe disease had reduced neutrophils and lymphocytes; severe coagulation dysfunction; altered content of biochemical factors (such as urea, lactate dehydrogenase); elevated high sensitivity C-reactive protein levels, neutrophil–lymphocyte, platelet-lymphocyte, and derived neutrophil–lymphocyte ratios, high sensitivity C-reactive protein-prealbumin ratio (HsCPAR), systemic immune-inflammation index, and high sensitivity C-reactive protein-albumin ratio (HsCAR); and low lymphocyte-monocyte ratio, prognostic nutritional index (PNI), and albumin-to-fibrinogen ratio. PNI, HsCAR, and HsCPAR correlated with the risk of severe disease. The nomogram combining the three parameters showed good discrimination with a C-index of 0.873 and reliable calibration. Moreover, HsCAR and HsCPAR correlated with duration of hospital stay. CONCLUSION: Taken together, PNI, HsCAR, and HsCPAR may serve as accurate biomarkers for the prediction of disease severity in patients with COVID-19 upon admission/hospitalization. Elsevier B.V. 2020-12 2020-10-03 /pmc/articles/PMC7532789/ /pubmed/33045571 http://dx.doi.org/10.1016/j.intimp.2020.107065 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 | Article Xue, Guohui Gan, Xing Wu, Zhiqiang Xie, Dan Xiong, Yan Hua, Lin Zhou, Bing Zhou, Nanjin Xiang, Jie Li, Junming Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19 |
title | Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19 |
title_full | Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19 |
title_fullStr | Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19 |
title_full_unstemmed | Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19 |
title_short | Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19 |
title_sort | novel serological biomarkers for inflammation in predicting disease severity in patients with covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532789/ https://www.ncbi.nlm.nih.gov/pubmed/33045571 http://dx.doi.org/10.1016/j.intimp.2020.107065 |
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