Literature DB >> 31992863

Do we have enough ophthalmologists to manage vision-threatening diabetic retinopathy? A global perspective.

Zhen Ling Teo1, Yih-Chung Tham1,2, Marco Yu1, Ching-Yu Cheng1,2,3, Tien Yin Wong1,2,3, Charumathi Sabanayagam4,5.   

Abstract

We aimed to estimate the supply of ophthalmologists in relation to the global and regional burden of vision-threatening diabetic retinopathy (VTDR). Diabetes mellitus (DM) population data from seven world regions were obtained from the International Diabetes Federation Atlas 2017. A systematic review was performed to include population-, community-based studies that reported country-specific VTDR prevalence. Random effect meta-analysis was then performed to estimate global and regional VTDR prevalence. VTDR prevalence estimates coupled with DM population data were then used to estimate the number of VTDR cases. Global and regional number of ophthalmologists were derived from the International Council of Ophthalmology Report 2015. Fifty studies (17 from Western Pacific [WP], nine North America and Caribbean [NAC], nine Middle East and North Africa [MENA], five Europe, eight South East Asia [SEA], one South and Central America [SACA] and one from Africa) were included. Global VTDR prevalence was 7.26% (95% CI, 6.18-8.32%). Regional VTDR prevalence was 14.35% in Africa, 11.21% in MENA, 10.00% in NAC, 6.32% in Europe, 6.22% in WP, 5.83% in SACA and 2.97% in SEA. Globally, there were 7.16 ophthalmologists per 1000 VTDR patients. Europe had the highest ophthalmologist per 1000 VTDR patient ratio at 18.03 followed by SACA (17.41), while NAC, MENA and Africa had the lowest at 4.90, 4.81 and 0.91 respectively. Across regions, the ophthalmologist densities ranged from 0.91 to 18.03 per 1000 VTDR patients, with NAC, MENA and Africa having less than 5 ophthalmologists per 1000 patients. These findings will aid global and regional policy planning and healthcare resource allocation for VTDR management.

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Year:  2020        PMID: 31992863      PMCID: PMC7314752          DOI: 10.1038/s41433-020-0776-5

Source DB:  PubMed          Journal:  Eye (Lond)        ISSN: 0950-222X            Impact factor:   3.775


  10 in total

1.  A new handheld fundus camera combined with visual artificial intelligence facilitates diabetic retinopathy screening.

Authors:  Shang Ruan; Yang Liu; Wei-Ting Hu; Hui-Xun Jia; Shan-Shan Wang; Min-Lu Song; Meng-Xi Shen; Da-Wei Luo; Tao Ye; Feng-Hua Wang
Journal:  Int J Ophthalmol       Date:  2022-04-18       Impact factor: 1.779

2.  Validation of diagnostic accuracy of retinal image grading by trained non-ophthalmologist grader for detecting diabetic retinopathy and diabetic macular edema.

Authors:  Sanil Joseph; Renu P Rajan; Balagiri Sundar; Soundarya Venkatachalam; John H Kempen; Ramasamy Kim
Journal:  Eye (Lond)       Date:  2022-07-29       Impact factor: 4.456

3.  Ophthalmic surgery in New Zealand: analysis of 410,099 surgical procedures and nationwide surgical intervention rates from 2009 to 2018.

Authors:  Ruhella R Hossain; Stephen Guest; Henry B Wallace; James McKelvie
Journal:  Eye (Lond)       Date:  2022-07-29       Impact factor: 4.456

Review 4.  Impact and Trends in Global Ophthalmology.

Authors:  Lloyd B Williams; S Grace Prakalapakorn; Zubair Ansari; Raquel Goldhardt
Journal:  Curr Ophthalmol Rep       Date:  2020-06-22

5.  Validation of an Automated Screening System for Diabetic Retinopathy Operating under Real Clinical Conditions.

Authors:  Soledad Jimenez-Carmona; Pedro Alemany-Marquez; Pablo Alvarez-Ramos; Eduardo Mayoral; Manuel Aguilar-Diosdado
Journal:  J Clin Med       Date:  2021-12-21       Impact factor: 4.241

6.  Screening Referable Diabetic Retinopathy Using a Semi-automated Deep Learning Algorithm Assisted Approach.

Authors:  Yueye Wang; Danli Shi; Zachary Tan; Yong Niu; Yu Jiang; Ruilin Xiong; Guankai Peng; Mingguang He
Journal:  Front Med (Lausanne)       Date:  2021-11-25

Review 7.  Understanding Neurodegeneration from a Clinical and Therapeutic Perspective in Early Diabetic Retinopathy.

Authors:  Serena Fragiotta; Maria D Pinazo-Durán; Gianluca Scuderi
Journal:  Nutrients       Date:  2022-02-14       Impact factor: 5.717

8.  Application of artificial intelligence-based dual-modality analysis combining fundus photography and optical coherence tomography in diabetic retinopathy screening in a community hospital.

Authors:  Rui Liu; Qingchen Li; Feiping Xu; Shasha Wang; Jie He; Yiting Cao; Fei Shi; Xinjian Chen; Jili Chen
Journal:  Biomed Eng Online       Date:  2022-07-20       Impact factor: 3.903

9.  Transition from Laser to Intravitreal Injections for Diabetic Retinopathy: Hospital Utilization and Costs from an Extended Healthcare Perspective.

Authors:  Silvia Nanjala Walekhwa Hertzberg; Øystein K Jørstad; Beáta Éva Petrovski; Ragnheidur Bragadottir; Leif Arthur Steffensen; Morten Carstens Moe; Emily A Burger; Goran Petrovski
Journal:  Int J Environ Res Public Health       Date:  2022-10-02       Impact factor: 4.614

Review 10.  The Role of Telemedicine, In-Home Testing and Artificial Intelligence to Alleviate an Increasingly Burdened Healthcare System: Diabetic Retinopathy.

Authors:  Janusz Pieczynski; Patrycja Kuklo; Andrzej Grzybowski
Journal:  Ophthalmol Ther       Date:  2021-06-22
  10 in total

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