Literature DB >> 32113513

Screening for diabetic retinopathy: new perspectives and challenges.

Stela Vujosevic1, Stephen J Aldington2, Paolo Silva3, Cristina Hernández4, Peter Scanlon2, Tunde Peto5, Rafael Simó6.   

Abstract

Although the prevalence of all stages of diabetic retinopathy has been declining since 1980 in populations with improved diabetes control, the crude prevalence of visual impairment and blindness caused by diabetic retinopathy worldwide increased between 1990 and 2015, largely because of the increasing prevalence of type 2 diabetes, particularly in low-income and middle-income countries. Screening for diabetic retinopathy is essential to detect referable cases that need timely full ophthalmic examination and treatment to avoid permanent visual loss. In the past few years, personalised screening intervals that take into account several risk factors have been proposed, with good cost-effectiveness ratios. However, resources for nationwide screening programmes are scarce in many countries. New technologies, such as scanning confocal ophthalmology with ultrawide field imaging and handheld mobile devices, teleophthalmology for remote grading, and artificial intelligence for automated detection and classification of diabetic retinopathy, are changing screening strategies and improving cost-effectiveness. Additionally, emerging evidence suggests that retinal imaging could be useful for identifying individuals at risk of cardiovascular disease or cognitive impairment, which could expand the role of diabetic retinopathy screening beyond the prevention of sight-threatening disease.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Year:  2020        PMID: 32113513     DOI: 10.1016/S2213-8587(19)30411-5

Source DB:  PubMed          Journal:  Lancet Diabetes Endocrinol        ISSN: 2213-8587            Impact factor:   32.069


  52 in total

Review 1.  Exosomes: Biomarkers and Therapeutic Targets of Diabetic Vascular Complications.

Authors:  Anqi Chen; Hailing Wang; Ying Su; Chunlin Zhang; Yanmei Qiu; Yifan Zhou; Yan Wan; Bo Hu; Yanan Li
Journal:  Front Endocrinol (Lausanne)       Date:  2021-08-12       Impact factor: 5.555

Review 2.  Diagnostic accuracy and potential covariates of artificial intelligence for diagnosing orthopedic fractures: a systematic literature review and meta-analysis.

Authors:  Xiang Zhang; Yi Yang; Yi-Wei Shen; Ke-Rui Zhang; Ze-Kun Jiang; Li-Tai Ma; Chen Ding; Bei-Yu Wang; Yang Meng; Hao Liu
Journal:  Eur Radiol       Date:  2022-06-27       Impact factor: 7.034

3.  Prevalence of long-term complications in inpatients with diabetes mellitus in China: a nationwide tertiary hospital-based study.

Authors:  Yihao Liu; Xin Ning; Luyao Zhang; Jianyan Long; Ruiming Liang; Sui Peng; Haibo Wang; Yanbing Li; Wei Chen; Haipeng Xiao
Journal:  BMJ Open Diabetes Res Care       Date:  2022-05

Review 4.  Diabetic retinopathy for the non-ophthalmologist.

Authors:  Timothy Hm Fung; Bakula Patel; Emma G Wilmot; Winfried Mk Amoaku
Journal:  Clin Med (Lond)       Date:  2022-03       Impact factor: 5.410

5.  CD146 as a promising therapeutic target for retinal and choroidal neovascularization diseases.

Authors:  Bai Xue; Ping Wang; Wenzhen Yu; Jing Feng; Jie Li; Rulian Zhao; Zhenglin Yang; Xiyun Yan; Hongxia Duan
Journal:  Sci China Life Sci       Date:  2021-10-29       Impact factor: 10.372

6.  A Network Pharmacology to Explore the Mechanism of Astragalus Membranaceus in the Treatment of Diabetic Retinopathy.

Authors:  Qi Jin; Xiao-Feng Hao; Li-Ke Xie; Jing Xu; Mei Sun; Hang Yuan; Shi-Hui Wang; Gai-Ping Wu; Meng-Lu Miao
Journal:  Evid Based Complement Alternat Med       Date:  2020-11-02       Impact factor: 2.629

7.  Diabetic Retinopathy Screening Using Artificial Intelligence and Handheld Smartphone-Based Retinal Camera.

Authors:  Fernando Korn Malerbi; Rafael Ernane Andrade; Paulo Henrique Morales; José Augusto Stuchi; Diego Lencione; Jean Vitor de Paulo; Mayana Pereira Carvalho; Fabrícia Silva Nunes; Roseanne Montargil Rocha; Daniel A Ferraz; Rubens Belfort
Journal:  J Diabetes Sci Technol       Date:  2021-01-12

8.  A Multitask Deep-Learning System to Classify Diabetic Macular Edema for Different Optical Coherence Tomography Devices: A Multicenter Analysis.

Authors:  Fangyao Tang; Xi Wang; An-Ran Ran; Carmen K M Chan; Mary Ho; Wilson Yip; Alvin L Young; Jerry Lok; Simon Szeto; Jason Chan; Fanny Yip; Raymond Wong; Ziqi Tang; Dawei Yang; Danny S Ng; Li Jia Chen; Marten Brelén; Victor Chu; Kenneth Li; Tracy H T Lai; Gavin S Tan; Daniel S W Ting; Haifan Huang; Haoyu Chen; Jacey Hongjie Ma; Shibo Tang; Theodore Leng; Schahrouz Kakavand; Suria S Mannil; Robert T Chang; Gerald Liew; Bamini Gopinath; Timothy Y Y Lai; Chi Pui Pang; Peter H Scanlon; Tien Yin Wong; Clement C Tham; Hao Chen; Pheng-Ann Heng; Carol Y Cheung
Journal:  Diabetes Care       Date:  2021-07-27       Impact factor: 17.152

9.  Andalusian program for early detection of diabetic retinopathy: implementation and 15-year follow-up of a population-based screening program in Andalusia, Southern Spain.

Authors:  Rafael Rodriguez-Acuña; Eduardo Mayoral; Manuel Aguilar-Diosdado; Reyes Rave; Beatriz Oyarzabal; Carmen Lama; Ana Carriazo; Maria Asuncion Martinez-Brocca
Journal:  BMJ Open Diabetes Res Care       Date:  2020-10

10.  Artificial intelligence-enabled screening for diabetic retinopathy: a real-world, multicenter and prospective study.

Authors:  Yifei Zhang; Juan Shi; Ying Peng; Zhiyun Zhao; Qidong Zheng; Zilong Wang; Kun Liu; Shengyin Jiao; Kexin Qiu; Ziheng Zhou; Li Yan; Dong Zhao; Hongwei Jiang; Yuancheng Dai; Benli Su; Pei Gu; Heng Su; Qin Wan; Yongde Peng; Jianjun Liu; Ling Hu; Tingyu Ke; Lei Chen; Fengmei Xu; Qijuan Dong; Demetri Terzopoulos; Guang Ning; Xun Xu; Xiaowei Ding; Weiqing Wang
Journal:  BMJ Open Diabetes Res Care       Date:  2020-10
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