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Performance of the AIDRScreening system in detecting diabetic retinopathy in the fundus photographs of Chinese patients: a prospective, multicenter, clinical study

BACKGROUND: Diabetic retinopathy (DR) is the leading cause of blindness in the working-age population worldwide, and there is a large unmet need for DR screening in China. This observational, prospective, multicenter, gold standard-controlled study sought to evaluate the effectiveness and safety of...

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Autores principales: Yang, Yao, Pan, Jianying, Yuan, Miner, Lai, Kunbei, Xie, Huirui, Ma, Li, Xu, Suzhong, Deng, Ruzhi, Zhao, Mingwei, Luo, Yan, Lin, Xiaofeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652560/
https://www.ncbi.nlm.nih.gov/pubmed/36388839
http://dx.doi.org/10.21037/atm-22-350
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author Yang, Yao
Pan, Jianying
Yuan, Miner
Lai, Kunbei
Xie, Huirui
Ma, Li
Xu, Suzhong
Deng, Ruzhi
Zhao, Mingwei
Luo, Yan
Lin, Xiaofeng
author_facet Yang, Yao
Pan, Jianying
Yuan, Miner
Lai, Kunbei
Xie, Huirui
Ma, Li
Xu, Suzhong
Deng, Ruzhi
Zhao, Mingwei
Luo, Yan
Lin, Xiaofeng
author_sort Yang, Yao
collection PubMed
description BACKGROUND: Diabetic retinopathy (DR) is the leading cause of blindness in the working-age population worldwide, and there is a large unmet need for DR screening in China. This observational, prospective, multicenter, gold standard-controlled study sought to evaluate the effectiveness and safety of the AIDRScreening system (v. 1.0), which is an artificial intelligence (AI)-enabled system that detects DR in the Chinese population based on fundus photographs. METHODS: Participants with diabetes mellitus (DM) were recruited. Fundus photographs (field 1 and field 2) of 1 eye in each participant were graded by the AIDRScreening system (v. 1.0) to detect referable DR (RDR). The results were compared to those of the masked manual grading (gold standard) system by the Zhongshan Image Reading Center. The primary outcomes were the sensitivity and specificity of the AIDRScreening system in detecting RDR. The other outcomes evaluated included the system’s diagnostic accuracy, positive predictive value, negative predictive value, diagnostic accuracy gain rate, and average diagnostic time gain rate. RESULTS: Among the 1,001 enrolled participants with DM, 962 (96.1%) were included in the final analyses. The participants had a median age of 60.61 years (range: 20.18–85.78 years), and 48.2% were men. The manual grading system detected RDR in 399 (41.48%) participants. The AIDRScreening system had a sensitivity of 86.72% (95% CI: 83.39–90.05%) and a specificity of 96.09% (95% CI: 94.14–97.54%) in the detection of RDR, and a false-positive rate of 3.91%. The diagnostic accuracy gain rate of the AIDRScreening system was 16.57% higher than that of the investigator, while the average diagnostic time gain rate was −37.32% lower. CONCLUSIONS: The automated AIDRScreening system can detect RDR with high accuracy, but cannot detect maculopathy. The implementation of the AIDRScreening system may increase the efficiency of DR screening.
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spelling pubmed-96525602022-11-15 Performance of the AIDRScreening system in detecting diabetic retinopathy in the fundus photographs of Chinese patients: a prospective, multicenter, clinical study Yang, Yao Pan, Jianying Yuan, Miner Lai, Kunbei Xie, Huirui Ma, Li Xu, Suzhong Deng, Ruzhi Zhao, Mingwei Luo, Yan Lin, Xiaofeng Ann Transl Med Original Article BACKGROUND: Diabetic retinopathy (DR) is the leading cause of blindness in the working-age population worldwide, and there is a large unmet need for DR screening in China. This observational, prospective, multicenter, gold standard-controlled study sought to evaluate the effectiveness and safety of the AIDRScreening system (v. 1.0), which is an artificial intelligence (AI)-enabled system that detects DR in the Chinese population based on fundus photographs. METHODS: Participants with diabetes mellitus (DM) were recruited. Fundus photographs (field 1 and field 2) of 1 eye in each participant were graded by the AIDRScreening system (v. 1.0) to detect referable DR (RDR). The results were compared to those of the masked manual grading (gold standard) system by the Zhongshan Image Reading Center. The primary outcomes were the sensitivity and specificity of the AIDRScreening system in detecting RDR. The other outcomes evaluated included the system’s diagnostic accuracy, positive predictive value, negative predictive value, diagnostic accuracy gain rate, and average diagnostic time gain rate. RESULTS: Among the 1,001 enrolled participants with DM, 962 (96.1%) were included in the final analyses. The participants had a median age of 60.61 years (range: 20.18–85.78 years), and 48.2% were men. The manual grading system detected RDR in 399 (41.48%) participants. The AIDRScreening system had a sensitivity of 86.72% (95% CI: 83.39–90.05%) and a specificity of 96.09% (95% CI: 94.14–97.54%) in the detection of RDR, and a false-positive rate of 3.91%. The diagnostic accuracy gain rate of the AIDRScreening system was 16.57% higher than that of the investigator, while the average diagnostic time gain rate was −37.32% lower. CONCLUSIONS: The automated AIDRScreening system can detect RDR with high accuracy, but cannot detect maculopathy. The implementation of the AIDRScreening system may increase the efficiency of DR screening. AME Publishing Company 2022-10 /pmc/articles/PMC9652560/ /pubmed/36388839 http://dx.doi.org/10.21037/atm-22-350 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Yang, Yao
Pan, Jianying
Yuan, Miner
Lai, Kunbei
Xie, Huirui
Ma, Li
Xu, Suzhong
Deng, Ruzhi
Zhao, Mingwei
Luo, Yan
Lin, Xiaofeng
Performance of the AIDRScreening system in detecting diabetic retinopathy in the fundus photographs of Chinese patients: a prospective, multicenter, clinical study
title Performance of the AIDRScreening system in detecting diabetic retinopathy in the fundus photographs of Chinese patients: a prospective, multicenter, clinical study
title_full Performance of the AIDRScreening system in detecting diabetic retinopathy in the fundus photographs of Chinese patients: a prospective, multicenter, clinical study
title_fullStr Performance of the AIDRScreening system in detecting diabetic retinopathy in the fundus photographs of Chinese patients: a prospective, multicenter, clinical study
title_full_unstemmed Performance of the AIDRScreening system in detecting diabetic retinopathy in the fundus photographs of Chinese patients: a prospective, multicenter, clinical study
title_short Performance of the AIDRScreening system in detecting diabetic retinopathy in the fundus photographs of Chinese patients: a prospective, multicenter, clinical study
title_sort performance of the aidrscreening system in detecting diabetic retinopathy in the fundus photographs of chinese patients: a prospective, multicenter, clinical study
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652560/
https://www.ncbi.nlm.nih.gov/pubmed/36388839
http://dx.doi.org/10.21037/atm-22-350
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