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9/10/2021 9:32:16 AM | Browse: 45 | Download: 33
Publication Name World Journal of Clinical Infectious Diseases
Manuscript ID 65056
Country/Territory China
Category Infectious Diseases
Manuscript Type Meta-Analysis
Article Title Lymphocyte count predicts the severity of COVID-19: Evidence from a meta-analysis
Manuscript Source Unsolicited Manuscript
All Author List Yi-Si Zhao and Ying-Xi Yu
Funding Agency and Grant Number
Corresponding Author Yi-Si Zhao, MM, Doctor, Department of Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi road, Yuzhong District, Chongqing 400016, China. 476663973@qq.com
Key Words COVID-19; Lymphocyte count; Coronavirus; Severe of disease; Meta-analysis
Core Tip Lymphocyte count reflects immune function and inflammatory state of body with infectious disease. Severe acute respiratory syndrome coronavirus 2 spreads and invades through respiratory mucosa, triggers a series of immune responses and induces cytokine storm in vivo, resulting in changes in immune components such as lymphocytes. Previous studies have shown that the decrease in lymphocyte count can be used as an indicator of severity for both severe acute respiratory syndrome and Middle East respiratory syndrome, both of which are coronavirus infections. Therefore, this paper systematically reviews and meta-analysis the literature evaluating the diagnostic and prognostic utility of the lymphocyte count in patients with viral pneumonia by coronavirus infections.
Citation Zhao YS, Yu YX. Lymphocyte count predicts the severity of COVID-19: Evidence from a meta-analysis. World J Clin Infect Dis 2021; In press
2021-02-27 12:05
Peer-Review Started
2021-02-27 12:20
To Make the First Decision
Return for Revision
2021-03-31 05:32
2021-04-03 14:30
Second Decision
2021-09-09 03:22
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2021-09-10 09:32
Articles in Press
2021-09-10 09:32
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
ISSN 2220-3176 (online)
Open Access This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Copyright © The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Assistant Editor Assistant Editor
Science Editor Man Liu
Reviewer Code 00503536, and 00503536
Editorial Director
Journal Chief Editor
Company Chief Editor Lian-Sheng Ma
Language Editor
Production Editor
Responsible Production Editor
Responsible Science Editor
Proofing Editorial Director Jin-Lei Wang
Proofing Editor-in-Chief Lian-Sheng Ma
Manuscript File 65056_Auto_Edited.docx
Answering Reviewers 65056-Answering reviewers.pdf
Audio Core Tip 65056-Audio core tip.m4a
Biostatistics Review Certificate 65056-Biostatistics statement.pdf
Conflict-of-Interest Disclosure Form 65056-Conflict-of-interest statement.pdf
Copyright License Agreement 65056-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate 65056-Language certificate.pdf
Supplementary Material 65056-Supplementary material.pdf
Peer-review Report 65056-Peer-review(s).pdf
Scientific Misconduct Check 65056-Bing-Ma YJ-1.jpg
Scientific Misconduct Check 65056-Bing-Liu M-2.png
Scientific Editor Work List 65056-Scientific editor work list.pdf