Evaluation of Automated Teleretinal Screening Program for Diabetic Retinopathy

医学 糖尿病性视网膜病变 眼底摄影 人口 眼底(子宫) 眼科 视网膜病变 回顾性队列研究 验光服务 糖尿病 视网膜 外科 荧光血管造影 环境卫生 内分泌学
作者
O. Bennett Walton,Robert B. Garoon,Christina Y. Weng,Jacob Gross,Alex K. Young,Kathryn A. Camero,Haoxing D. Jin,Petros Carvounis,Robert E. Coffee,Yvonne I. Chu
出处
期刊:JAMA Ophthalmology [American Medical Association]
卷期号:134 (2): 204-204 被引量:92
标识
DOI:10.1001/jamaophthalmol.2015.5083
摘要

Diabetic retinopathy is a leading cause of blindness, but its detrimental effects are preventable with early detection and treatment. Screening for diabetic retinopathy has the potential to increase the number of cases treated early, especially in populations with limited access to care.To determine the efficacy of an automated algorithm in interpreting screening ophthalmoscopic photographs from patients with diabetes compared with a reading center interpretation.Retrospective cohort analysis of 15,015 patients with type 1 or 2 diabetes in the Harris Health System in Harris County, Texas, who had undergone a retinal screening examination and nonmydriatic fundus photography via the Intelligent Retinal Imaging System (IRIS) from June 2013 to April 2014 were included. The IRIS-based interpretations were compared with manual interpretation. The IRIS algorithm population statistics were calculated.Sensitivity and false-negative rate of the IRIS computer-based algorithm compared with reading center interpretation of the same images.A total of 15 015 consecutive patients (aged 18-98 years); mean 54.3 years with known type 1 or 2 diabetes underwent nonmydriatic fundus photography for a diabetic retinopathy screening examination. The sensitivity of the IRIS algorithm in detecting sight-threatening diabetic eye disease compared with the reading center interpretation was 66.4% (95% CI, 62.8%-69.9%) with a false-negative rate of 2%. The specificity was 72.8% (95% CI, 72.0%-73.5%). In a population where 15.8% of people with diabetes have sight-threatening diabetic eye disease, the IRIS algorithm positive predictive value was 10.8% (95% CI, 9.6%-11.9%) and the negative predictive value was 97.8% (95% CI, 96.8%-98.6%).In this large urban setting, the IRIS computer algorithm-based screening program had a high sensitivity and a low false-negative rate, suggesting that it may be an effective alternative to conventional reading center image interpretation. The IRIS algorithm shows promise as a screening program, but algorithm refinement is needed to achieve better performance. Further studies of patient safety, cost-effectiveness, and widespread applications of this type of algorithm should be pursued to better understand the role of teleretinal imaging and automated analysis in the global health care system.
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