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Prognostic Value of Inflammatory Biomarkers in Patients with Severe COVID-19: A Single-Center Retrospective Study

BACKGROUND: The current knowledge about novel coronavirus-2019 (COVID-19) indicates that the immune system and inflammatory response play a crucial role in the severity and prognosis of the disease. In this study, we aimed to investigate prognostic value of systemic inflammatory biomarkers including...

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Autores principales: Açıksarı, Gönül, Koçak, Mehmet, Çağ, Yasemin, Altunal, Lütfiye Nilsun, Atıcı, Adem, Çelik, Fatma Betül, Bölen, Furkan, Açıksarı, Kurtuluş, Çalışkan, Mustafa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236773/
https://www.ncbi.nlm.nih.gov/pubmed/34248354
http://dx.doi.org/10.1177/11772719211027022
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author Açıksarı, Gönül
Koçak, Mehmet
Çağ, Yasemin
Altunal, Lütfiye Nilsun
Atıcı, Adem
Çelik, Fatma Betül
Bölen, Furkan
Açıksarı, Kurtuluş
Çalışkan, Mustafa
author_facet Açıksarı, Gönül
Koçak, Mehmet
Çağ, Yasemin
Altunal, Lütfiye Nilsun
Atıcı, Adem
Çelik, Fatma Betül
Bölen, Furkan
Açıksarı, Kurtuluş
Çalışkan, Mustafa
author_sort Açıksarı, Gönül
collection PubMed
description BACKGROUND: The current knowledge about novel coronavirus-2019 (COVID-19) indicates that the immune system and inflammatory response play a crucial role in the severity and prognosis of the disease. In this study, we aimed to investigate prognostic value of systemic inflammatory biomarkers including C-reactive protein/albumin ratio (CAR), prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) in patients with severe COVID-19. METHODS: This single-center, retrospective study included a total of 223 patients diagnosed with severe COVID-19. Primary outcome measure was mortality during hospitalization. Multivariate logistic regression analyses were performed to identify independent predictors associated with mortality in patients with severe COVID-19. Receiver operating characteristic (ROC) curve was used to determine cut-offs, and area under the curve (AUC) values were used to demonstrate discriminative ability of biomarkers. RESULTS: Compared to survivors of severe COVID-19, non-survivors had higher CAR, NLR, and PLR, and lower LMR and lower PNI (P < .05 for all). The optimal CAR, PNI, NLR, PLR, and LMR cut-off values for detecting prognosis were 3.4, 40.2, 6. 27, 312, and 1.54 respectively. The AUC values of CAR, PNI, NLR, PLR, and LMR for predicting hospital mortality in patients with severe COVID-19 were 0.81, 0.91, 0.85, 0.63, and 0.65, respectively. In ROC analysis, comparative discriminative ability of CAR, PNI, and NLR for hospital mortality were superior to PLR and LMR. Multivariate analysis revealed that CAR (⩾0.34, P = .004), NLR (⩾6.27, P = .012), and PNI (⩽40.2, P = .009) were independent predictors associated with mortality in severe COVID-19 patients. CONCLUSIONS: The CAR, PNI, and NLR are independent predictors of mortality in hospitalized severe COVID-19 patients and are more closely associated with prognosis than PLR or LMR.
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spelling pubmed-82367732021-07-08 Prognostic Value of Inflammatory Biomarkers in Patients with Severe COVID-19: A Single-Center Retrospective Study Açıksarı, Gönül Koçak, Mehmet Çağ, Yasemin Altunal, Lütfiye Nilsun Atıcı, Adem Çelik, Fatma Betül Bölen, Furkan Açıksarı, Kurtuluş Çalışkan, Mustafa Biomark Insights Biomarker Research - Future Planning, Future Proofing BACKGROUND: The current knowledge about novel coronavirus-2019 (COVID-19) indicates that the immune system and inflammatory response play a crucial role in the severity and prognosis of the disease. In this study, we aimed to investigate prognostic value of systemic inflammatory biomarkers including C-reactive protein/albumin ratio (CAR), prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) in patients with severe COVID-19. METHODS: This single-center, retrospective study included a total of 223 patients diagnosed with severe COVID-19. Primary outcome measure was mortality during hospitalization. Multivariate logistic regression analyses were performed to identify independent predictors associated with mortality in patients with severe COVID-19. Receiver operating characteristic (ROC) curve was used to determine cut-offs, and area under the curve (AUC) values were used to demonstrate discriminative ability of biomarkers. RESULTS: Compared to survivors of severe COVID-19, non-survivors had higher CAR, NLR, and PLR, and lower LMR and lower PNI (P < .05 for all). The optimal CAR, PNI, NLR, PLR, and LMR cut-off values for detecting prognosis were 3.4, 40.2, 6. 27, 312, and 1.54 respectively. The AUC values of CAR, PNI, NLR, PLR, and LMR for predicting hospital mortality in patients with severe COVID-19 were 0.81, 0.91, 0.85, 0.63, and 0.65, respectively. In ROC analysis, comparative discriminative ability of CAR, PNI, and NLR for hospital mortality were superior to PLR and LMR. Multivariate analysis revealed that CAR (⩾0.34, P = .004), NLR (⩾6.27, P = .012), and PNI (⩽40.2, P = .009) were independent predictors associated with mortality in severe COVID-19 patients. CONCLUSIONS: The CAR, PNI, and NLR are independent predictors of mortality in hospitalized severe COVID-19 patients and are more closely associated with prognosis than PLR or LMR. SAGE Publications 2021-06-24 /pmc/articles/PMC8236773/ /pubmed/34248354 http://dx.doi.org/10.1177/11772719211027022 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Biomarker Research - Future Planning, Future Proofing
Açıksarı, Gönül
Koçak, Mehmet
Çağ, Yasemin
Altunal, Lütfiye Nilsun
Atıcı, Adem
Çelik, Fatma Betül
Bölen, Furkan
Açıksarı, Kurtuluş
Çalışkan, Mustafa
Prognostic Value of Inflammatory Biomarkers in Patients with Severe COVID-19: A Single-Center Retrospective Study
title Prognostic Value of Inflammatory Biomarkers in Patients with Severe COVID-19: A Single-Center Retrospective Study
title_full Prognostic Value of Inflammatory Biomarkers in Patients with Severe COVID-19: A Single-Center Retrospective Study
title_fullStr Prognostic Value of Inflammatory Biomarkers in Patients with Severe COVID-19: A Single-Center Retrospective Study
title_full_unstemmed Prognostic Value of Inflammatory Biomarkers in Patients with Severe COVID-19: A Single-Center Retrospective Study
title_short Prognostic Value of Inflammatory Biomarkers in Patients with Severe COVID-19: A Single-Center Retrospective Study
title_sort prognostic value of inflammatory biomarkers in patients with severe covid-19: a single-center retrospective study
topic Biomarker Research - Future Planning, Future Proofing
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236773/
https://www.ncbi.nlm.nih.gov/pubmed/34248354
http://dx.doi.org/10.1177/11772719211027022
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