Retrospective Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Diabetes. Jun 15, 2024; 15(6): 1242-1253
Published online Jun 15, 2024. doi: 10.4239/wjd.v15.i6.1242
Developing and validating a predictive model of delivering large-for-gestational-age infants among women with gestational diabetes mellitus
Yi-Tian Zhu, Lan-Lan Xiang, Ya-Jun Chen, Tian-Ying Zhong, Jun-Jun Wang, Yu Zeng
Yi-Tian Zhu, Jun-Jun Wang, Department of Clinical Laboratory, Jinling Clinical Medical College of Nanjing Medical University, Nanjing 210002, Jiangsu Province, China
Yi-Tian Zhu, Lan-Lan Xiang, Ya-Jun Chen, Tian-Ying Zhong, Yu Zeng, Department of Clinical Laboratory, Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital, Nanjing 210003, Jiangsu Province, China
Co-first authors: Yi-Tian Zhu and Lan-Lan Xiang.
Co-corresponding authors: Yu Zeng and Jun-Jun Wang.
Author contributions: Zhu YT, Xiang LL and Zeng Y wrote the main manuscript; Zhu YT and Xiang LL collected the study data; Chen YJ and Zhong TY performed the statistical analysis; Wang JJ and Zeng Y supervised and conceived the idea of this work. All the authors read and approved the final manuscript. Zhu YT and Xiang LL as co-first authors have made outstanding contributions in data collection, organization, analysis, and paper writing. Their rigorous scientific attitude, solid medical knowledge, and exceptional team collaboration skills have ensured the accuracy and reliability of the research data, as well as the depth and comprehensiveness of the paper's content. Additionally, they actively participated in the medical editing process, ensuring that the language expression of the paper is precise, fluent, and compliant with the writing standards for medical papers. Meanwhile, co-corresponding authors Zeng Y and Wang JJ made significant contributions in research design, method selection, data analysis, and paper interpretation. As experts from different medical fields, they provided valuable interdisciplinary advice and guidance for the research work, enabling a deeper and more comprehensive exploration of medical issues. Choosing Zhu YT and Xiang LL as co-first authors, along with Zeng Y and Wang JJ as co-corresponding authors, is not only a recognition of their individual contributions but also an acknowledgment of their teamwork spirit. This team structure not only reflects the cohesion within the research team but also demonstrates the professionalism and diversity of the team members in their respective medical fields.
Supported by National Natural Science Foundation of China, No. 81870546; Nanjing Medical Science and Technique Development Foundation, No. YKK23151; and Science and Technology Development Foundation Item of Nanjing Medical University, No. NMUB20210117.
Institutional review board statement: The study was reviewed and approved by the Medical Ethics Committee of Women’s Hospital of Nanjing Medical University, Nanjing Women and Children’s Healthcare Hospital (No. 2022KY-068).
Informed consent statement: Informed consent was waived by the Medical Ethics Committee of Nanjing Women and Children’s Healthcare Hospital due to the review of the study.
Conflict-of-interest statement: The authors declare no conflicts of interest.
Data sharing statement: No additional data are available.
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/
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, Qinhuai District, Nanjing 210003, Jiangsu Province, China. zengyu@njmu.edu.cn
Received: January 25, 2024
Revised: March 5, 2024
Accepted: April 25, 2024
Published online: June 15, 2024
Processing time: 138 Days and 5.5 Hours
Core Tip

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.