深度学习糖尿病视网膜病变算法在印度的表现。

IF 10.5 1区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Arthur Brant, Preeti Singh, Xiang Yin, Lu Yang, Jay Nayar, Divleen Jeji, Yossi Matias, Greg S Corrado, Dale R Webster, Sunny Virmani, Anchintha Meenu, Naresh Babu Kannan, Jonathan Krause, Florence Thng, Lily Peng, Yun Liu, Kasumi Widner, Kim Ramasamy
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引用次数: 0

摘要

重要性:虽然前瞻性研究已经调查了人工智能(AI)检测糖尿病视网膜病变(DR)和糖尿病黄斑水肿(DME)的准确性,但迄今为止,关于这些算法临床表现的公开数据很少。目的:评价自动视网膜疾病评估(ARDA)算法在印度Aravind眼科医院部署后的临床表现。设计、环境和参与者:这项横断面分析涉及使用ARDA筛选的患者眼底照片的大约1%样本。通过美国眼科医生对DR和DME的裁决对图像进行分级,并将ARDA的输出与印度南部45个地点的裁决等级进行比较。患者在2019年1月1日至2023年7月31日期间随机选择。主要结局和指标:主要分析ARDA对严重非增殖性DR (NPDR)或增殖性DR (PDR)的敏感性和特异性。二次分析的重点是视力威胁DR (STDR) (DME或严重NPDR或PDR)的敏感性和特异性。结果:4537例患者共4537张分级图像,平均(SD)年龄为55.2(11.9)岁,男性2272例(50.1%)。在3941例可分级照片患者中,683例(17.3%)有任何DR, 146例(3.7%)有严重NPDR或PDR, 109例(2.8%)有PDR, 398例(10.1%)有STDR。ARDA对严重NPDR或PDR的敏感性和特异性分别为97.0% (95% CI, 92.6% ~ 99.2%)和96.4% (95% CI, 95.7% ~ 97.0%)。阳性预测值为50.7%,阴性预测值为99.9%。严重NPDR或PDR的临床重要漏报率为0%(例如,一些严重NPDR或PDR患者被解释为中度DR并转诊至临床)。ARDA对STDR的敏感性为95.9% (95% CI, 93.0% ~ 97.4%),特异性为94.9% (95% CI, 94.1% ~ 95.7%);PPV和NPV分别为67.9%和99.5%。结论及相关性:本横断面研究考察了ARDA的临床表现,对严重NPDR和PDR的敏感性和特异性均超过96%,对严重NPDR和PDR患者进行眼科转诊的检出率为100%。这份针对印度60万 万名患者筛查后ARDA表现的初步大规模上市后报告强调了监测和公布算法临床表现的重要性,这与监管机构的建议是一致的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance of a Deep Learning Diabetic Retinopathy Algorithm in India.

Importance: While prospective studies have investigated the accuracy of artificial intelligence (AI) for detection of diabetic retinopathy (DR) and diabetic macular edema (DME), to date, little published data exist on the clinical performance of these algorithms.

Objective: To evaluate the clinical performance of an automated retinal disease assessment (ARDA) algorithm in the postdeployment setting at Aravind Eye Hospital in India.

Design, setting, and participants: This cross-sectional analysis involved an approximate 1% sample of fundus photographs from patients screened using ARDA. Images were graded via adjudication by US ophthalmologists for DR and DME, and ARDA's output was compared against the adjudicated grades at 45 sites in Southern India. Patients were randomly selected between January 1, 2019, and July 31, 2023.

Main outcomes and measures: Primary analyses were the sensitivity and specificity of ARDA for severe nonproliferative DR (NPDR) or proliferative DR (PDR). Secondary analyses focused on sensitivity and specificity for sight-threatening DR (STDR) (DME or severe NPDR or PDR).

Results: Among the 4537 patients with 4537 images with adjudicated grades, mean (SD) age was 55.2 (11.9) years and 2272 (50.1%) were male. Among the 3941 patients with gradable photographs, 683 (17.3%) had any DR, 146 (3.7%) had severe NPDR or PDR, 109 (2.8%) had PDR, and 398 (10.1%) had STDR. ARDA's sensitivity and specificity for severe NPDR or PDR were 97.0% (95% CI, 92.6%-99.2%) and 96.4% (95% CI, 95.7%-97.0%), respectively. Positive predictive value (PPV) was 50.7% and negative predictive value (NPV) was 99.9%. The clinically important miss rate for severe NPDR or PDR was 0% (eg, some patients with severe NPDR or PDR were interpreted as having moderate DR and referred to clinic). ARDA's sensitivity for STDR was 95.9% (95% CI, 93.0%-97.4%) and specificity was 94.9% (95% CI, 94.1%-95.7%); PPV and NPV were 67.9% and 99.5%, respectively.

Conclusions and relevance: In this cross-sectional study investigating the clinical performance of ARDA, sensitivity and specificity for severe NPDR and PDR exceeded 96% and caught 100% of patients with severe  NPDR and PDR for ophthalmology referral. This preliminary large-scale postmarketing report of the performance of ARDA after screening 600 000 patients in India underscores the importance of monitoring and publication an algorithm's clinical performance, consistent with recommendations by regulatory bodies.

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来源期刊
JAMA Network Open
JAMA Network Open Medicine-General Medicine
CiteScore
16.00
自引率
2.90%
发文量
2126
审稿时长
16 weeks
期刊介绍: JAMA Network Open, a member of the esteemed JAMA Network, stands as an international, peer-reviewed, open-access general medical journal.The publication is dedicated to disseminating research across various health disciplines and countries, encompassing clinical care, innovation in health care, health policy, and global health. JAMA Network Open caters to clinicians, investigators, and policymakers, providing a platform for valuable insights and advancements in the medical field. As part of the JAMA Network, a consortium of peer-reviewed general medical and specialty publications, JAMA Network Open contributes to the collective knowledge and understanding within the medical community.
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