Editorial
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Diabetes. May 15, 2025; 16(5): 103316
Published online May 15, 2025. doi: 10.4239/wjd.v16.i5.103316
Various classification methods for diabetes mellitus in the management of blood glucose control
Qing Jiang, Yun Hu, Jian-Hua Ma
Qing Jiang, Department of Endocrinology, The Affiliated Geriatric Hospital of Nanjing Medical University, Nanjing 210000, Jiangsu Province, China
Yun Hu, Department of Endocrinology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi 214000, Jiangsu Province, China
Jian-Hua Ma, Department of Endocrinology, Nanjing First Hospital, Nanjing 210000, Jiangsu Province, China
Author contributions: Jiang Q and Hu Y drafted the initial manuscript; Ma JH conceptualized and revised the manuscript.
Conflict-of-interest statement: All the authors have no conflict of interest related to the manuscript.
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: Jian-Hua Ma, MD, Professor, Department of Endocrinology, Nanjing First Hospital, No. 32 Gongqingtuan Road, Nanjing 210000, Jiangsu Province, China. majianhua@china.com
Received: November 28, 2024
Revised: February 23, 2025
Accepted: February 26, 2025
Published online: May 15, 2025
Processing time: 161 Days and 14.4 Hours
Core Tip

Core Tip: The prevalence of diabetes is increasing, and blood glucose control is of utmost importance. This article explores various diabetes mellitus classification methods, for example, incorporating phenotypic subtypes, genetic subtypes, and soft clustering, and highlights the limitations of traditional classification methods. Updated classification methods can help develop personalised treatment plans, which are important for optimal diabetes management.