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Evaluation of simple and cost-effective immuno- haematological markers to predict outcome in hospitalized severe COVID-19 patients, with a focus on diabetes mellitus - A retrospective study in Andhra Pradesh, India
BACKGROUND AND AIMS: COVID-19 pandemic has strained the health infrastructure globally, providing an opportunity to identify cost-effective biomarkers. We aimed to identify simple hematological prognostic markers in hospitalized severe COVID-19 patients with and without diabetes. METHODS: Retrospect...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Diabetes India. Published by Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006494/ https://www.ncbi.nlm.nih.gov/pubmed/33819728 http://dx.doi.org/10.1016/j.dsx.2021.03.025 |
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author | Ramesh, Jayanthy Reddy, S.L. Sagar Rajesh, Moganti Varghese, Johann |
author_facet | Ramesh, Jayanthy Reddy, S.L. Sagar Rajesh, Moganti Varghese, Johann |
author_sort | Ramesh, Jayanthy |
collection | PubMed |
description | BACKGROUND AND AIMS: COVID-19 pandemic has strained the health infrastructure globally, providing an opportunity to identify cost-effective biomarkers. We aimed to identify simple hematological prognostic markers in hospitalized severe COVID-19 patients with and without diabetes. METHODS: Retrospective study of RT-PCR confirmed hospitalized severe COVID-19 patients (total: n = 154 patients, including diabetic subset n = 57) were analyzed. Clinically applicable cut-offs were derived using receiver operating characteristic (ROC) curve analysis for total leucocyte count (TLC), absolute neutrophil count (ANC), neutrophil lymphocyte ratio (NLR), and derived neutrophil lymphocyte ratio (dNLR) in order to prognosticate the outcome. RESULTS: Among 154 severe COVID-19 patients, significant association with mortality was seen with respect to TLC(p < 0.001), ANC (p < 0.001), NLR(p < 0.001) and dNLR(p < 0.001). In the total cohort, applicable cut-offs based on ROC curve in predicting outcome were, for TLC 8950 cells/mm(3) (area under curve (AUC)-0.764, odds ratio (OR)-7.53), ANC 7679 cells/mm(3) (AUC-0.789, OR-8.14), NLR 5.13 (AUC-0.741, OR-4.77), dNLR 3.44 (AUC -0.741, OR-4.43) respectively.In diabetic subset, the cut-offs for TLC was 8950 cells/mm(3) (AUC -0.762, OR-14.9), ANC 6510 cells/mm(3) (AUC -0.773, OR-16.8), NLR 5.13(AUC -0.678, OR-6) and dNLR 3.25(AUC -0.685, OR-4.7) respectively. CONCLUSIONS: In severe COVID-19 patients irrespective of diabetes, a simple, applicable total leucocyte count cut-off, 8950 cells/mm(3) , together with easily derived cut-offs for ANC, NLR, dNLR may serve as cost-effective prognosticators of clinical outcome. A normal TLC may be misleading in the intensive care and the above applicable cut-off for TLC serves as an early warning tool for high-risk identification and better in-hospital management. Even with similar or lower cut-offs, diabetics had a higher mortality. |
format | Online Article Text |
id | pubmed-8006494 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Diabetes India. Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80064942021-03-29 Evaluation of simple and cost-effective immuno- haematological markers to predict outcome in hospitalized severe COVID-19 patients, with a focus on diabetes mellitus - A retrospective study in Andhra Pradesh, India Ramesh, Jayanthy Reddy, S.L. Sagar Rajesh, Moganti Varghese, Johann Diabetes Metab Syndr Article BACKGROUND AND AIMS: COVID-19 pandemic has strained the health infrastructure globally, providing an opportunity to identify cost-effective biomarkers. We aimed to identify simple hematological prognostic markers in hospitalized severe COVID-19 patients with and without diabetes. METHODS: Retrospective study of RT-PCR confirmed hospitalized severe COVID-19 patients (total: n = 154 patients, including diabetic subset n = 57) were analyzed. Clinically applicable cut-offs were derived using receiver operating characteristic (ROC) curve analysis for total leucocyte count (TLC), absolute neutrophil count (ANC), neutrophil lymphocyte ratio (NLR), and derived neutrophil lymphocyte ratio (dNLR) in order to prognosticate the outcome. RESULTS: Among 154 severe COVID-19 patients, significant association with mortality was seen with respect to TLC(p < 0.001), ANC (p < 0.001), NLR(p < 0.001) and dNLR(p < 0.001). In the total cohort, applicable cut-offs based on ROC curve in predicting outcome were, for TLC 8950 cells/mm(3) (area under curve (AUC)-0.764, odds ratio (OR)-7.53), ANC 7679 cells/mm(3) (AUC-0.789, OR-8.14), NLR 5.13 (AUC-0.741, OR-4.77), dNLR 3.44 (AUC -0.741, OR-4.43) respectively.In diabetic subset, the cut-offs for TLC was 8950 cells/mm(3) (AUC -0.762, OR-14.9), ANC 6510 cells/mm(3) (AUC -0.773, OR-16.8), NLR 5.13(AUC -0.678, OR-6) and dNLR 3.25(AUC -0.685, OR-4.7) respectively. CONCLUSIONS: In severe COVID-19 patients irrespective of diabetes, a simple, applicable total leucocyte count cut-off, 8950 cells/mm(3) , together with easily derived cut-offs for ANC, NLR, dNLR may serve as cost-effective prognosticators of clinical outcome. A normal TLC may be misleading in the intensive care and the above applicable cut-off for TLC serves as an early warning tool for high-risk identification and better in-hospital management. Even with similar or lower cut-offs, diabetics had a higher mortality. Diabetes India. Published by Elsevier Ltd. 2021 2021-03-29 /pmc/articles/PMC8006494/ /pubmed/33819728 http://dx.doi.org/10.1016/j.dsx.2021.03.025 Text en © 2021 Diabetes India. Published by Elsevier Ltd. 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 Ramesh, Jayanthy Reddy, S.L. Sagar Rajesh, Moganti Varghese, Johann Evaluation of simple and cost-effective immuno- haematological markers to predict outcome in hospitalized severe COVID-19 patients, with a focus on diabetes mellitus - A retrospective study in Andhra Pradesh, India |
title | Evaluation of simple and cost-effective immuno- haematological markers to predict outcome in hospitalized severe COVID-19 patients, with a focus on diabetes mellitus - A retrospective study in Andhra Pradesh, India |
title_full | Evaluation of simple and cost-effective immuno- haematological markers to predict outcome in hospitalized severe COVID-19 patients, with a focus on diabetes mellitus - A retrospective study in Andhra Pradesh, India |
title_fullStr | Evaluation of simple and cost-effective immuno- haematological markers to predict outcome in hospitalized severe COVID-19 patients, with a focus on diabetes mellitus - A retrospective study in Andhra Pradesh, India |
title_full_unstemmed | Evaluation of simple and cost-effective immuno- haematological markers to predict outcome in hospitalized severe COVID-19 patients, with a focus on diabetes mellitus - A retrospective study in Andhra Pradesh, India |
title_short | Evaluation of simple and cost-effective immuno- haematological markers to predict outcome in hospitalized severe COVID-19 patients, with a focus on diabetes mellitus - A retrospective study in Andhra Pradesh, India |
title_sort | evaluation of simple and cost-effective immuno- haematological markers to predict outcome in hospitalized severe covid-19 patients, with a focus on diabetes mellitus - a retrospective study in andhra pradesh, india |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8006494/ https://www.ncbi.nlm.nih.gov/pubmed/33819728 http://dx.doi.org/10.1016/j.dsx.2021.03.025 |
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