| 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: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| 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
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Endocrinology & Metabolism |
| Manuscript Type |
Review |
| Article Title |
Digital health technologies for diabetes-centered five-condition co-management in China: Theoretical foundations, practical experience, and technical challenges
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Jia-Li Xu, Cheng Luo, Cheng-Zheng Duan, Shi-Yu Xu, Zhi-Qiang Wu, Li-Ya Ye, Zhi-Peng Li, Mao-Sen Wang, Xian-Mei Yu and Dong-Juan He |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Quzhou Science and Technology Bureau |
2025K114 |
|
| Corresponding Author |
Dong-Juan He, Dean, MD, Professor, Department of Endocrinology, The Second People’s Hospital of Quzhou, No. 338 Xin’an Avenue, Qujiang District, Quzhou 324000, Zhejiang Province, China. hedongjuan1247@wmu.edu.cn |
| Key Words |
Artificial intelligence; Cardiometabolic risk; Chronic disease management; Digital health; Dyslipidemia; Hypertension; Hyperuricemia; Obesity; Precision medicine; Type 2 diabetes mellitus |
| Core Tip |
Diabetes-centered five-condition co-management integrates glycemic control with concurrent management of hypertension, dyslipidemia, hyperuricemia, and obesity to address shared cardiometabolic pathophysiology and synergistic risk amplification. This review synthesizes the epidemiologic rationale, mechanistic links, and evidence from digital health-enabled care models, highlighting how continuous monitoring, personalized decision support, and multidisciplinary workflows can improve target attainment and adherence. We propose a practical implementation framework with measurable endpoints, risk stratification, and governance requirements for artificial intelligence tools, while outlining barriers such as interoperability, equity, and long-term safety and effectiveness evaluation in real-world settings. |
| Publish Date |
2026-07-09 06:58 |
| Citation |
Xu JL, Luo C, Duan CZ, Xu SY, Wu ZQ, Ye LY, Li ZP, Wang MS, Yu XM, He DJ. Digital health technologies for diabetes-centered five-condition co-management in China: Theoretical foundations, practical experience, and technical challenges. World J Diabetes 2026; 17(7): 119712
|
| URL |
https://www.wjgnet.com/1948-9358/full/v17/i7/119712.htm |
| DOI |
https://doi.org/10.4239/wjd.119712 |
