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Evaluation of Hematological Parameters in Predicting Intensive Care Unit Admission in COVID-19 Patients
Hematological parameters like total leukocyte count (TLC), neutrophil, lymphocyte, and absolute eosinophil counts (AEC), and neutrophil-to-lymphocyte ratio (NLR) are known to predict the severity of novel coronavirus disease 2019 (COVID-19) patients. In the present study, we aimed to study the role...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8761838/ https://www.ncbi.nlm.nih.gov/pubmed/35071985 http://dx.doi.org/10.1007/s42399-021-01115-8 |
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author | Saurabh, Animesh Dey, Biswajit Raphael, Vandana Barman, Bhupen Dev, Priyanka Tiewsoh, Iadarilang Lyngdoh, Bifica Sofia Dutta, Kaustuv |
author_facet | Saurabh, Animesh Dey, Biswajit Raphael, Vandana Barman, Bhupen Dev, Priyanka Tiewsoh, Iadarilang Lyngdoh, Bifica Sofia Dutta, Kaustuv |
author_sort | Saurabh, Animesh |
collection | PubMed |
description | Hematological parameters like total leukocyte count (TLC), neutrophil, lymphocyte, and absolute eosinophil counts (AEC), and neutrophil-to-lymphocyte ratio (NLR) are known to predict the severity of novel coronavirus disease 2019 (COVID-19) patients. In the present study, we aimed to study the role of complete blood count parameters in triaging these patients requiring intensive care unit (ICU) admission. A retrospective study was done over a period of 2 months. Patients, who were ≥ 18 years of age with COVID-19 confirmed on SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) and whose routine hematology counts were sent within 24 h of admission, were included in the study. Cut-off values of 47.5 years for age, 11.3 × 10(9)/L for TLC, and 9.1 for NLR were predictive of disease severity among COVID-19 patients. Relative neutrophilia ≥ 70% (p < 0.007), relative lymphopenia ≤ 20% (p < 0.002), AEC ≤ 40/cumm (p < 0.001), and NLR ≥ 9.1 (p < 0.001) were significantly associated with ICU admission. Routine hematological parameters are cost-effective and fast predictive markers for severe COVID-19 patients, especially in resource-constrained health care settings to utilize limited ICU resources more effectively. |
format | Online Article Text |
id | pubmed-8761838 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-87618382022-01-18 Evaluation of Hematological Parameters in Predicting Intensive Care Unit Admission in COVID-19 Patients Saurabh, Animesh Dey, Biswajit Raphael, Vandana Barman, Bhupen Dev, Priyanka Tiewsoh, Iadarilang Lyngdoh, Bifica Sofia Dutta, Kaustuv SN Compr Clin Med Original Paper Hematological parameters like total leukocyte count (TLC), neutrophil, lymphocyte, and absolute eosinophil counts (AEC), and neutrophil-to-lymphocyte ratio (NLR) are known to predict the severity of novel coronavirus disease 2019 (COVID-19) patients. In the present study, we aimed to study the role of complete blood count parameters in triaging these patients requiring intensive care unit (ICU) admission. A retrospective study was done over a period of 2 months. Patients, who were ≥ 18 years of age with COVID-19 confirmed on SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) and whose routine hematology counts were sent within 24 h of admission, were included in the study. Cut-off values of 47.5 years for age, 11.3 × 10(9)/L for TLC, and 9.1 for NLR were predictive of disease severity among COVID-19 patients. Relative neutrophilia ≥ 70% (p < 0.007), relative lymphopenia ≤ 20% (p < 0.002), AEC ≤ 40/cumm (p < 0.001), and NLR ≥ 9.1 (p < 0.001) were significantly associated with ICU admission. Routine hematological parameters are cost-effective and fast predictive markers for severe COVID-19 patients, especially in resource-constrained health care settings to utilize limited ICU resources more effectively. Springer International Publishing 2022-01-17 2022 /pmc/articles/PMC8761838/ /pubmed/35071985 http://dx.doi.org/10.1007/s42399-021-01115-8 Text en © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Paper Saurabh, Animesh Dey, Biswajit Raphael, Vandana Barman, Bhupen Dev, Priyanka Tiewsoh, Iadarilang Lyngdoh, Bifica Sofia Dutta, Kaustuv Evaluation of Hematological Parameters in Predicting Intensive Care Unit Admission in COVID-19 Patients |
title | Evaluation of Hematological Parameters in Predicting Intensive Care Unit Admission in COVID-19 Patients |
title_full | Evaluation of Hematological Parameters in Predicting Intensive Care Unit Admission in COVID-19 Patients |
title_fullStr | Evaluation of Hematological Parameters in Predicting Intensive Care Unit Admission in COVID-19 Patients |
title_full_unstemmed | Evaluation of Hematological Parameters in Predicting Intensive Care Unit Admission in COVID-19 Patients |
title_short | Evaluation of Hematological Parameters in Predicting Intensive Care Unit Admission in COVID-19 Patients |
title_sort | evaluation of hematological parameters in predicting intensive care unit admission in covid-19 patients |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8761838/ https://www.ncbi.nlm.nih.gov/pubmed/35071985 http://dx.doi.org/10.1007/s42399-021-01115-8 |
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