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6/11/2024 2:35:34 PM | Browse: 105 | Download: 626
Publication Name World Journal of Diabetes
Manuscript ID 92404
Country China
Received
2024-01-25 09:10
Peer-Review Started
2024-01-25 09:10
First Decision by Editorial Office Director
2024-02-27 04:06
Return for Revision
2024-02-27 04:06
Revised
2024-03-05 14:40
Publication Fee Transferred
Second Decision by Editor
2024-04-17 09:11
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director
2024-04-25 08:14
Articles in Press
2024-04-25 08:14
Edit the Manuscript by Language Editor
Typeset the Manuscript
2024-05-22 09:55
Publish the Manuscript Online
2024-06-11 14:35
ISSN 1948-9358 (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: https://creativecommons.org/Licenses/by-nc/4.0/
Copyright © The Author(s) 2024. 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 Obstetrics & Gynecology
Manuscript Type Retrospective Study
Article Title Developing and validating a predictive model of delivering large-for-gestational-age infants among women with gestational diabetes mellitus
Manuscript Source Invited Manuscript
All Author List Yi-Tian Zhu, Lan-Lan Xiang, Ya-Jun Chen, Tian-Ying Zhong, Jun-Jun Wang and Yu Zeng
ORCID
Author(s) ORCID Number
Yi-Tian Zhu http://orcid.org/0000-0002-2627-6350
Lan-Lan Xiang http://orcid.org/0000-0001-9404-4132
Jun-Jun Wang http://orcid.org/0000-0003-0507-1724
Yu Zeng http://orcid.org/0000-0002-9978-8883
Funding Agency and Grant Number
Funding Agency Grant Number
National Natural Science Foundation of China 81870546
Nanjing Medical Science and Technique Development Foundation YKK23151
Science and Technology Development Foundation Item of Nanjing Medical University NMUB20210117
Corresponding Author Yu Zeng, PhD, Professor, Department of Clinical Laboratory, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, No. 123 Tianfei Lane, Mochou Road, Qinhuan District, Nanjing 210003, Jiangsu Province, China. zengyu@njmu.edu.cn
Key Words Large-for-gestational-age; Gestational diabetes mellitus; Predictive model; Nomogram; Triglyceride-glucose index
Core Tip Gestational diabetes mellitus (GDM) is a global problem, and the prevalence of large-for-gestational-age (LGA) is increasing. Early prediction of LGA can enable timely intervention and improve pregnancy outcomes. We developed and validated a predictive nomogram for pregnant women with GDM at risk of delivering an LGA infant. Four demographic parameters and second-trimester maternal serum biochemical markers were identified. The nomogram effectively stratified women with GDM in their second trimester based on their risk of delivering LGA infants.
Publish Date 2024-06-11 14:35
Citation

Zhu YT, Xiang LL, Chen YJ, Zhong TY, Wang JJ, Zeng Y. Developing and validating a predictive model of delivering large-for-gestational-age infants among women with gestational diabetes mellitus. World J Diabetes 2024; 15(6): 1242-1253

URL https://www.wjgnet.com/1948-9358/full/v15/i6/1242.htm
DOI https://dx.doi.org/10.4239/wjd.v15.i6.1242
Full Article (PDF) WJD-15-1242-with-cover.pdf
Manuscript File 92404_Auto_Edited-YJP.docx
Answering Reviewers 92404-answering-reviewers.pdf
Audio Core Tip 92404-audio.m4a
Biostatistics Review Certificate 92404-biostatistics-statement.pdf
Conflict-of-Interest Disclosure Form 92404-conflict-of-interest-statement.pdf
Copyright License Agreement 92404-copyright-assignment.pdf
Signed Informed Consent Form(s) or Document(s) 92404-informed-consent-statement.pdf
Institutional Review Board Approval Form or Document 92404-institutional-review-board-statement.pdf
Non-Native Speakers of English Editing Certificate 92404-non-native-speakers.pdf
Supplementary Material 92404-supplementary-material.pdf
Peer-review Report 92404-peer-reviews.pdf
Scientific Misconduct Check 92404-scientific-misconduct-check.jpg
Scientific Editor Work List 92404-scientific-editor-work-list.pdf
CrossCheck Report 92404-crosscheck-report.pdf