SYSTEMATIC REVIEW article
Front. Endocrinol.
Sec. Clinical Diabetes
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1556049
This article is part of the Research TopicPrevention and Treatment Advancements in Diabetic RetinopathyView all 13 articles
Risk prediction models for diabetic retinopathy: a systematic review
Provisionally accepted
- 1Chengdu University of Traditional Chinese Medicine, Chengdu, China
- 2Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan Province, China
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Background: Diabetic retinopathy, a prevalent complication of diabetes mellitus, is a growing public health concern. The use of robust predictive models can aid healthcare professionals in identifying high-risk patients, enabling them to implement early intervention and treatment strategies.Objective: To systematically evaluate published prediction models for diabetic retinopathy, select better prediction models for healthcare professionals, and provide a valuable reference for model optimization.Methods: A comprehensive search was conducted across the PubMed, Web of Science, Embase, and the Cochrane Library databases for relevant literature on predictive models for diabetic retinopathy. The search period was set from the time of library construction to November 14, 2023. Furthermore, risk of bias and
Keywords: ：Diabetes, Diabetic retinopathy (DR), Predictive Modeling, Risk factors, Systematic review
Received: 06 Jan 2025; Accepted: 25 Jun 2025.
Copyright: © 2025 Huang, Wu, Ye, Li, Chen and Huang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yingmin Wu, Chengdu University of Traditional Chinese Medicine, Chengdu, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.