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Characteristics of lymphocyte subsets and cytokine profiles of patients with COVID-19

BACKGROUND: Abnormalities of lymphocyte subsets and cytokine profiles have been observed in most patients with coronavirus disease (COVID-19). Here, we explore the role of lymphocyte subsets and cytokines on hospital admission in predicting the severity of COVID-19. METHODS: This study included 214...

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Autores principales: Pan, Pengfei, Du, Xinxin, Zhou, Qilong, Cui, Yong, Deng, Xiaochun, Liu, Chao, Hu, Zongjun, Chen, Jianguo, Yu, Xiangyou, Shi, Weihua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8960102/
https://www.ncbi.nlm.nih.gov/pubmed/35346253
http://dx.doi.org/10.1186/s12985-022-01786-2
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author Pan, Pengfei
Du, Xinxin
Zhou, Qilong
Cui, Yong
Deng, Xiaochun
Liu, Chao
Hu, Zongjun
Chen, Jianguo
Yu, Xiangyou
Shi, Weihua
author_facet Pan, Pengfei
Du, Xinxin
Zhou, Qilong
Cui, Yong
Deng, Xiaochun
Liu, Chao
Hu, Zongjun
Chen, Jianguo
Yu, Xiangyou
Shi, Weihua
author_sort Pan, Pengfei
collection PubMed
description BACKGROUND: Abnormalities of lymphocyte subsets and cytokine profiles have been observed in most patients with coronavirus disease (COVID-19). Here, we explore the role of lymphocyte subsets and cytokines on hospital admission in predicting the severity of COVID-19. METHODS: This study included 214 patients with COVID-19 who were treated at Chongqing University Three Gorges Hospital from January 19, 2020 to April 30, 2020. Any mutants were not detected in the studied patients. Patients were divided into non-intensive care unit (ICU) (mild/moderate) group and ICU (severe/critical) group, according to the severity of the disease. Clinical and laboratory data, including peripheral lymphocyte subsets and cytokines, were analyzed and compared. Logistic regression was used to analyze the predictive factors for ICU admission. Receiver operating characteristic (ROC) curves were drawn to evaluate the predictive value of selected indicators for the severity of COVID-19. RESULTS: Of the 214 patients enrolled, 161 were non-ICU patients and 53 were ICU patients. Lymphopenia was observed in nearly all of ICU patients (96.2%) and 84.5% of non-ICU patients on hospital admission. The absolute number of lymphocytes, CD3(+) T cells, CD4(+) T cells, CD8(+) T cells, CD19(+) B cells, and natural killer (NK) cells were lower in ICU group (659.00 × 10(6)/L, 417.00 × 10(6)/L, 261.00 × 10(6)/L, 140.00 × 10(6)/L, 109.00 × 10(6)/L, 102.00 × 10(6)/L, respectively) than in non-ICU group (1063.00 × 10(9)/L, 717.00 × 10(6)/L, 432.00 × 10(6)/L, 271.00 × 10(6)/L, 133.00 × 10(6)/L, 143.00 × 10(6)/L, respectively). Interleukin (IL)-6 was significantly higher in ICU patients than in non-ICU patients (18.08 pg/mL vs. 3.13 pg/mL, P < 0.001). Multivariate logistic regression analysis showed that age (odds ratio: 1.067 [1.034–1.101]), diabetes mellitus (odds ratio: 9.154 [2.710–30.926]), CD3(+) T cells (odds ratio: 0.996 [0.994–0.997]), and IL-6 (odds ratio: 1.006 [1.000–1.013]) were independent predictors for the development of severe disease. ROC curve analysis showed that the area under the ROC curve (AUC) of CD3(+) T cells and IL-6 was 0.806 (0.737–0.874) and 0.785 (0.705–0.864), respectively, and the cutoff values were 510.50 × 10(6)/L (sensitivity, 71.7%; specificity, 79.5%) and 6.58 pg/mL (77.4%, 74.5%), respectively. There were no statistical differences among all tested indicators of lymphocyte subsets and cytokines between severe group (n = 38) and critical group (n = 15) on hospital admission or ICU admission, respectively. CONCLUSIONS: The levels of lymphocyte subsets decreased and the level of IL-6 increased significantly in ICU COVID-19 patients compared with non-ICU COVID-19 patients. Therefore, the number of CD3(+) T cells and the level of IL-6 on hospital admission may serve as predictive factors for identifying patients with wild-type virus infection who will have severe disease.
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spelling pubmed-89601022022-03-29 Characteristics of lymphocyte subsets and cytokine profiles of patients with COVID-19 Pan, Pengfei Du, Xinxin Zhou, Qilong Cui, Yong Deng, Xiaochun Liu, Chao Hu, Zongjun Chen, Jianguo Yu, Xiangyou Shi, Weihua Virol J Research BACKGROUND: Abnormalities of lymphocyte subsets and cytokine profiles have been observed in most patients with coronavirus disease (COVID-19). Here, we explore the role of lymphocyte subsets and cytokines on hospital admission in predicting the severity of COVID-19. METHODS: This study included 214 patients with COVID-19 who were treated at Chongqing University Three Gorges Hospital from January 19, 2020 to April 30, 2020. Any mutants were not detected in the studied patients. Patients were divided into non-intensive care unit (ICU) (mild/moderate) group and ICU (severe/critical) group, according to the severity of the disease. Clinical and laboratory data, including peripheral lymphocyte subsets and cytokines, were analyzed and compared. Logistic regression was used to analyze the predictive factors for ICU admission. Receiver operating characteristic (ROC) curves were drawn to evaluate the predictive value of selected indicators for the severity of COVID-19. RESULTS: Of the 214 patients enrolled, 161 were non-ICU patients and 53 were ICU patients. Lymphopenia was observed in nearly all of ICU patients (96.2%) and 84.5% of non-ICU patients on hospital admission. The absolute number of lymphocytes, CD3(+) T cells, CD4(+) T cells, CD8(+) T cells, CD19(+) B cells, and natural killer (NK) cells were lower in ICU group (659.00 × 10(6)/L, 417.00 × 10(6)/L, 261.00 × 10(6)/L, 140.00 × 10(6)/L, 109.00 × 10(6)/L, 102.00 × 10(6)/L, respectively) than in non-ICU group (1063.00 × 10(9)/L, 717.00 × 10(6)/L, 432.00 × 10(6)/L, 271.00 × 10(6)/L, 133.00 × 10(6)/L, 143.00 × 10(6)/L, respectively). Interleukin (IL)-6 was significantly higher in ICU patients than in non-ICU patients (18.08 pg/mL vs. 3.13 pg/mL, P < 0.001). Multivariate logistic regression analysis showed that age (odds ratio: 1.067 [1.034–1.101]), diabetes mellitus (odds ratio: 9.154 [2.710–30.926]), CD3(+) T cells (odds ratio: 0.996 [0.994–0.997]), and IL-6 (odds ratio: 1.006 [1.000–1.013]) were independent predictors for the development of severe disease. ROC curve analysis showed that the area under the ROC curve (AUC) of CD3(+) T cells and IL-6 was 0.806 (0.737–0.874) and 0.785 (0.705–0.864), respectively, and the cutoff values were 510.50 × 10(6)/L (sensitivity, 71.7%; specificity, 79.5%) and 6.58 pg/mL (77.4%, 74.5%), respectively. There were no statistical differences among all tested indicators of lymphocyte subsets and cytokines between severe group (n = 38) and critical group (n = 15) on hospital admission or ICU admission, respectively. CONCLUSIONS: The levels of lymphocyte subsets decreased and the level of IL-6 increased significantly in ICU COVID-19 patients compared with non-ICU COVID-19 patients. Therefore, the number of CD3(+) T cells and the level of IL-6 on hospital admission may serve as predictive factors for identifying patients with wild-type virus infection who will have severe disease. BioMed Central 2022-03-28 /pmc/articles/PMC8960102/ /pubmed/35346253 http://dx.doi.org/10.1186/s12985-022-01786-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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
Pan, Pengfei
Du, Xinxin
Zhou, Qilong
Cui, Yong
Deng, Xiaochun
Liu, Chao
Hu, Zongjun
Chen, Jianguo
Yu, Xiangyou
Shi, Weihua
Characteristics of lymphocyte subsets and cytokine profiles of patients with COVID-19
title Characteristics of lymphocyte subsets and cytokine profiles of patients with COVID-19
title_full Characteristics of lymphocyte subsets and cytokine profiles of patients with COVID-19
title_fullStr Characteristics of lymphocyte subsets and cytokine profiles of patients with COVID-19
title_full_unstemmed Characteristics of lymphocyte subsets and cytokine profiles of patients with COVID-19
title_short Characteristics of lymphocyte subsets and cytokine profiles of patients with COVID-19
title_sort characteristics of lymphocyte subsets and cytokine profiles of patients with covid-19
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8960102/
https://www.ncbi.nlm.nih.gov/pubmed/35346253
http://dx.doi.org/10.1186/s12985-022-01786-2
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