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9/28/2021 10:18:27 AM | Browse: 68 | Download: 178
Publication Name World Journal of Clinical Cases
Manuscript ID 66236
Country/Territory China
Received
2021-04-13 08:13
Peer-Review Started
2021-04-13 08:15
To Make the First Decision
Return for Revision
2021-05-11 17:48
Revised
2021-06-08 11:47
Second Decision
2021-08-16 03:29
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2021-08-16 06:20
Articles in Press
2021-08-16 06:20
Publication Fee Transferred
Edit the Manuscript by Language Editor
2021-09-01 02:58
Typeset the Manuscript
2021-09-23 15:08
Publish the Manuscript Online
2021-09-28 10:00
ISSN 2307-8960 (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.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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
Category Medical Informatics
Manuscript Type Observational Study
Article Title Validated tool for early prediction of intensive care unit admission in COVID-19 patients
Manuscript Source Unsolicited Manuscript
All Author List Hao-Fan Huang, Yong Liu, Jin-Xiu Li, Hui Dong, Shan Gao, Zheng-Yang Huang, Shou-Zhi Fu, Lu-Yu Yang, Hui-Zhi Lu, Liao-You Xia, Song Cao, Yi Gao and Xia-Xia Yu
Funding Agency and Grant Number
Funding Agency Grant Number
Shenzhen Municipal Government’s "Peacock Plan" KQTD2016053112051497
Corresponding Author Xia-Xia Yu, PhD, Assistant Professor, School of Biomedical Engineering, Health Science Center, Shenzhen University, No. 3688 Nanhai Avenue, Shenzhen 518060, Guangdong Province, China. xiaxiayu@szu.edu.cn
Key Words COVID-19; Intensive care units; Machine learning; Prognostic predictive model; Risk stratification
Core Tip This study established a risk stratification tool for the early prediction of intensive care unit (ICU) admission among coronavirus disease 2019 (COVID-19) patients at hospital admission to enable such patients to receive immediate appropriate care, thus improving medical resource allocation. The model with 13 indicators selected from 65 laboratory results collected at hospital admission could be used to assess the risk of ICU admission. This study provided a simple probability prediction model to identify ICU admission risk in COVID-19 patients at admission.
Publish Date 2021-09-28 10:00
Citation Huang HF, Liu Y, Li JX, Dong H, Gao S, Huang ZY, Fu SZ, Yang LY, Lu HZ, Xia LY, Cao S, Gao Y, Yu XX. Validated tool for early prediction of intensive care unit admission in COVID-19 patients. World J Clin Cases 2021; 9(28): 8388-8403
URL https://www.wjgnet.com/2307-8960/full/v9/i28/8388.htm
DOI https://dx.doi.org/10.12998/wjcc.v9.i28.8388
Full Article (PDF) WJCC-9-8388.pdf
Full Article (Word) WJCC-9-8388.docx
Manuscript File 66236-Review-Filipodia-CL.docx
Answering Reviewers 66236-Answering reviewers.pdf
Audio Core Tip 66236-Audio core tip.mp3
Biostatistics Review Certificate 66236-Biostatistics statement.pdf
Conflict-of-Interest Disclosure Form 66236-Conflict-of-interest statement.pdf
Copyright License Agreement 66236-Copyright license agreement.pdf
Signed Informed Consent Form(s) or Document(s) 66236-Informed consent statement.pdf
Institutional Review Board Approval Form or Document 66236-Institutional review board statement.pdf
Non-Native Speakers of English Editing Certificate 66236-Language certificate.pdf
Peer-review Report 66236-Peer-review(s).pdf
Scientific Misconduct Check 66236-Bing-Wang JL-1.jpg
Scientific Misconduct Check 66236-Bing-Wu YXJ-2.jpg
Scientific Misconduct Check 66236-Scientific misconduct check.pdf
Scientific Editor Work List 66236-Scientific editor work list.pdf