Retrospective Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Diabetes. Oct 15, 2023; 14(10): 1541-1550
Published online Oct 15, 2023. doi: 10.4239/wjd.v14.i10.1541
Establishment and evaluation of a risk prediction model for gestational diabetes mellitus
Qing Lin, Zhuan-Ji Fang
Qing Lin, Zhuan-Ji Fang, Department of Obstetrics, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics and Gynecology and Pediatrics, Fujian Medical University, Fuzhou 350001, Fujian Province, China
Author contributions: Lin Q designed and performed the research and wrote the paper; Fang ZJ designed the research and supervised the report.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of the Fujian Maternity and Child Health Hospital.
Informed consent statement: As the study used anonymous and pre-existing data, the requirement for the informed consent from patients was waived.
Conflict-of-interest statement: We have no financial relationships to disclose.
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: Zhuan-Ji Fang, MM, Associate Chief Physician, Department of Obstetrics, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics and Gynecology and Pediatrics, Fujian Medical University, No. 18 Daoshan Rd., Gulou Dist, Fuzhou 350001, Fujian Province, China. fzlqtg@163.com
Received: August 1, 2023
Peer-review started: August 1, 2023
First decision: August 16, 2023
Revised: August 21, 2023
Accepted: September 14, 2023
Article in press: September 14, 2023
Published online: October 15, 2023
Processing time: 69 Days and 10.6 Hours
Core Tip

Core Tip: Gestational diabetes mellitus (GDM) is a common pregnancy complication, which has an important impact on maternal and child health. Early prediction of GDM can result in timely interventions in patients and improve pregnancy outcomes. This study examined various risk factors associated with GDM and established and compared two prediction models: The nomogram model and the random forest model. The random forest model has good predictive ability, which can effectively predict the risk of GDM and provide accurate references for early prevention and management of GDM.