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Diagnostic Efficacy and Therapeutic Decision-making Capacity of an Artificial Intelligence Platform for Childhood Cataracts in Eye Clinics: A Multicentre Randomized Controlled Trial

BACKGROUND: CC-Cruiser is an artificial intelligence (AI) platform developed for diagnosing childhood cataracts and providing risk stratification and treatment recommendations. The high accuracy of CC-Cruiser was previously validated using specific datasets. The objective of this study was to compar...

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Autores principales: Lin, Haotian, Li, Ruiyang, Liu, Zhenzhen, Chen, Jingjing, Yang, Yahan, Chen, Hui, Lin, Zhuoling, Lai, Weiyi, Long, Erping, Wu, Xiaohang, Lin, Duoru, Zhu, Yi, Chen, Chuan, Wu, Dongxuan, Yu, Tongyong, Cao, Qianzhong, Li, Xiaoyan, Li, Jing, Li, Wangting, Wang, Jinghui, Yang, Mingmin, Hu, Huiling, Zhang, Li, Yu, Yang, Chen, Xuelan, Hu, Jianmin, Zhu, Ke, Jiang, Shuhong, Huang, Yalin, Tan, Gang, Huang, Jialing, Lin, Xiaoming, Zhang, Xinyu, Luo, Lixia, Liu, Yuhua, Liu, Xialin, Cheng, Bing, Zheng, Danying, Wu, Mingxing, Chen, Weirong, Liu, Yizhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510889/
https://www.ncbi.nlm.nih.gov/pubmed/31143882
http://dx.doi.org/10.1016/j.eclinm.2019.03.001
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author Lin, Haotian
Li, Ruiyang
Liu, Zhenzhen
Chen, Jingjing
Yang, Yahan
Chen, Hui
Lin, Zhuoling
Lai, Weiyi
Long, Erping
Wu, Xiaohang
Lin, Duoru
Zhu, Yi
Chen, Chuan
Wu, Dongxuan
Yu, Tongyong
Cao, Qianzhong
Li, Xiaoyan
Li, Jing
Li, Wangting
Wang, Jinghui
Yang, Mingmin
Hu, Huiling
Zhang, Li
Yu, Yang
Chen, Xuelan
Hu, Jianmin
Zhu, Ke
Jiang, Shuhong
Huang, Yalin
Tan, Gang
Huang, Jialing
Lin, Xiaoming
Zhang, Xinyu
Luo, Lixia
Liu, Yuhua
Liu, Xialin
Cheng, Bing
Zheng, Danying
Wu, Mingxing
Chen, Weirong
Liu, Yizhi
author_facet Lin, Haotian
Li, Ruiyang
Liu, Zhenzhen
Chen, Jingjing
Yang, Yahan
Chen, Hui
Lin, Zhuoling
Lai, Weiyi
Long, Erping
Wu, Xiaohang
Lin, Duoru
Zhu, Yi
Chen, Chuan
Wu, Dongxuan
Yu, Tongyong
Cao, Qianzhong
Li, Xiaoyan
Li, Jing
Li, Wangting
Wang, Jinghui
Yang, Mingmin
Hu, Huiling
Zhang, Li
Yu, Yang
Chen, Xuelan
Hu, Jianmin
Zhu, Ke
Jiang, Shuhong
Huang, Yalin
Tan, Gang
Huang, Jialing
Lin, Xiaoming
Zhang, Xinyu
Luo, Lixia
Liu, Yuhua
Liu, Xialin
Cheng, Bing
Zheng, Danying
Wu, Mingxing
Chen, Weirong
Liu, Yizhi
author_sort Lin, Haotian
collection PubMed
description BACKGROUND: CC-Cruiser is an artificial intelligence (AI) platform developed for diagnosing childhood cataracts and providing risk stratification and treatment recommendations. The high accuracy of CC-Cruiser was previously validated using specific datasets. The objective of this study was to compare the diagnostic efficacy and treatment decision-making capacity between CC-Cruiser and ophthalmologists in real-world clinical settings. METHODS: This multicentre randomized controlled trial was performed in five ophthalmic clinics in different areas across China. Pediatric patients (aged ≤ 14 years) without a definitive diagnosis of cataracts or history of previous eye surgery were randomized (1:1) to receive a diagnosis and treatment recommendation from either CC-Cruiser or senior consultants (with over 5 years of clinical experience in pediatric ophthalmology). The experts who provided a gold standard diagnosis, and the investigators who performed slit-lamp photography and data analysis were blinded to the group assignments. The primary outcome was the diagnostic performance for childhood cataracts with reference to cataract experts' standards. The secondary outcomes included the evaluation of disease severity and treatment determination, the time required for the diagnosis, and patient satisfaction, which was determined by the mean rating. This trial is registered with ClinicalTrials.gov (NCT03240848). FINDINGS: Between August 9, 2017 and May 25, 2018, 350 participants (700 eyes) were randomly assigned for diagnosis by CC-Cruiser (350 eyes) or senior consultants (350 eyes). The accuracies of cataract diagnosis and treatment determination were 87.4% and 70.8%, respectively, for CC-Cruiser, which were significantly lower than 99.1% and 96.7%, respectively, for senior consultants (p < 0.001, OR = 0.06 [95% CI 0.02 to 0.19]; and p < 0.001, OR = 0.08 [95% CI 0.03 to 0.25], respectively). The mean time for receiving a diagnosis from CC-Cruiser was 2.79 min, which was significantly less than 8.53 min for senior consultants (p < 0.001, mean difference 5.74 [95% CI 5.43 to 6.05]). The patients were satisfied with the overall medical service quality provided by CC-Cruiser, typically with its time-saving feature in cataract diagnosis. INTERPRETATION: CC-Cruiser exhibited less accurate performance comparing to senior consultants in diagnosing childhood cataracts and making treatment decisions. However, the medical service provided by CC-Cruiser was less time-consuming and achieved a high level of patient satisfaction. CC-Cruiser has the capacity to assist human doctors in clinical practice in its current state. FUNDING: National Key R&D Program of China (2018YFC0116500) and the Key Research Plan for the National Natural Science Foundation of China in Cultivation Project (91846109).
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spelling pubmed-65108892019-05-29 Diagnostic Efficacy and Therapeutic Decision-making Capacity of an Artificial Intelligence Platform for Childhood Cataracts in Eye Clinics: A Multicentre Randomized Controlled Trial Lin, Haotian Li, Ruiyang Liu, Zhenzhen Chen, Jingjing Yang, Yahan Chen, Hui Lin, Zhuoling Lai, Weiyi Long, Erping Wu, Xiaohang Lin, Duoru Zhu, Yi Chen, Chuan Wu, Dongxuan Yu, Tongyong Cao, Qianzhong Li, Xiaoyan Li, Jing Li, Wangting Wang, Jinghui Yang, Mingmin Hu, Huiling Zhang, Li Yu, Yang Chen, Xuelan Hu, Jianmin Zhu, Ke Jiang, Shuhong Huang, Yalin Tan, Gang Huang, Jialing Lin, Xiaoming Zhang, Xinyu Luo, Lixia Liu, Yuhua Liu, Xialin Cheng, Bing Zheng, Danying Wu, Mingxing Chen, Weirong Liu, Yizhi EClinicalMedicine Research Paper BACKGROUND: CC-Cruiser is an artificial intelligence (AI) platform developed for diagnosing childhood cataracts and providing risk stratification and treatment recommendations. The high accuracy of CC-Cruiser was previously validated using specific datasets. The objective of this study was to compare the diagnostic efficacy and treatment decision-making capacity between CC-Cruiser and ophthalmologists in real-world clinical settings. METHODS: This multicentre randomized controlled trial was performed in five ophthalmic clinics in different areas across China. Pediatric patients (aged ≤ 14 years) without a definitive diagnosis of cataracts or history of previous eye surgery were randomized (1:1) to receive a diagnosis and treatment recommendation from either CC-Cruiser or senior consultants (with over 5 years of clinical experience in pediatric ophthalmology). The experts who provided a gold standard diagnosis, and the investigators who performed slit-lamp photography and data analysis were blinded to the group assignments. The primary outcome was the diagnostic performance for childhood cataracts with reference to cataract experts' standards. The secondary outcomes included the evaluation of disease severity and treatment determination, the time required for the diagnosis, and patient satisfaction, which was determined by the mean rating. This trial is registered with ClinicalTrials.gov (NCT03240848). FINDINGS: Between August 9, 2017 and May 25, 2018, 350 participants (700 eyes) were randomly assigned for diagnosis by CC-Cruiser (350 eyes) or senior consultants (350 eyes). The accuracies of cataract diagnosis and treatment determination were 87.4% and 70.8%, respectively, for CC-Cruiser, which were significantly lower than 99.1% and 96.7%, respectively, for senior consultants (p < 0.001, OR = 0.06 [95% CI 0.02 to 0.19]; and p < 0.001, OR = 0.08 [95% CI 0.03 to 0.25], respectively). The mean time for receiving a diagnosis from CC-Cruiser was 2.79 min, which was significantly less than 8.53 min for senior consultants (p < 0.001, mean difference 5.74 [95% CI 5.43 to 6.05]). The patients were satisfied with the overall medical service quality provided by CC-Cruiser, typically with its time-saving feature in cataract diagnosis. INTERPRETATION: CC-Cruiser exhibited less accurate performance comparing to senior consultants in diagnosing childhood cataracts and making treatment decisions. However, the medical service provided by CC-Cruiser was less time-consuming and achieved a high level of patient satisfaction. CC-Cruiser has the capacity to assist human doctors in clinical practice in its current state. FUNDING: National Key R&D Program of China (2018YFC0116500) and the Key Research Plan for the National Natural Science Foundation of China in Cultivation Project (91846109). Elsevier 2019-03-17 /pmc/articles/PMC6510889/ /pubmed/31143882 http://dx.doi.org/10.1016/j.eclinm.2019.03.001 Text en © 2019 Published by Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Paper
Lin, Haotian
Li, Ruiyang
Liu, Zhenzhen
Chen, Jingjing
Yang, Yahan
Chen, Hui
Lin, Zhuoling
Lai, Weiyi
Long, Erping
Wu, Xiaohang
Lin, Duoru
Zhu, Yi
Chen, Chuan
Wu, Dongxuan
Yu, Tongyong
Cao, Qianzhong
Li, Xiaoyan
Li, Jing
Li, Wangting
Wang, Jinghui
Yang, Mingmin
Hu, Huiling
Zhang, Li
Yu, Yang
Chen, Xuelan
Hu, Jianmin
Zhu, Ke
Jiang, Shuhong
Huang, Yalin
Tan, Gang
Huang, Jialing
Lin, Xiaoming
Zhang, Xinyu
Luo, Lixia
Liu, Yuhua
Liu, Xialin
Cheng, Bing
Zheng, Danying
Wu, Mingxing
Chen, Weirong
Liu, Yizhi
Diagnostic Efficacy and Therapeutic Decision-making Capacity of an Artificial Intelligence Platform for Childhood Cataracts in Eye Clinics: A Multicentre Randomized Controlled Trial
title Diagnostic Efficacy and Therapeutic Decision-making Capacity of an Artificial Intelligence Platform for Childhood Cataracts in Eye Clinics: A Multicentre Randomized Controlled Trial
title_full Diagnostic Efficacy and Therapeutic Decision-making Capacity of an Artificial Intelligence Platform for Childhood Cataracts in Eye Clinics: A Multicentre Randomized Controlled Trial
title_fullStr Diagnostic Efficacy and Therapeutic Decision-making Capacity of an Artificial Intelligence Platform for Childhood Cataracts in Eye Clinics: A Multicentre Randomized Controlled Trial
title_full_unstemmed Diagnostic Efficacy and Therapeutic Decision-making Capacity of an Artificial Intelligence Platform for Childhood Cataracts in Eye Clinics: A Multicentre Randomized Controlled Trial
title_short Diagnostic Efficacy and Therapeutic Decision-making Capacity of an Artificial Intelligence Platform for Childhood Cataracts in Eye Clinics: A Multicentre Randomized Controlled Trial
title_sort diagnostic efficacy and therapeutic decision-making capacity of an artificial intelligence platform for childhood cataracts in eye clinics: a multicentre randomized controlled trial
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510889/
https://www.ncbi.nlm.nih.gov/pubmed/31143882
http://dx.doi.org/10.1016/j.eclinm.2019.03.001
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