Meredith Morgan Eye Center, University of California, Berkeley, USA.
EyePACS LLC, Santa Cruz, CA, USA.
J Diabetes Sci Technol. 2021 May;15(3):664-665. doi: 10.1177/1932296820914287. Epub 2020 Apr 24.
The study by Shah et al published in this issue of the validates the IDx autonomous diabetic retinopathy (DR) screening program in a real-world setting. The study found high sensitivity (100%) but low specificity (82%) for referable DR. The resulting positive predictive value of 19% means that four out of five patients without referable DR would be referred to ophthalmology causing a significant burden to ophthalmologists, primary care clinics, and patients. Artificial intelligence programs that provide better specificity, multiple levels of DR, and annotations of where lesions are located in the retina may function better than a simple referral/no referral output. This will allow for better engagement of patients through the difficult process of adhering to treatment recommendations and control their diabetes.
Shah 等人在本期杂志上发表的研究在真实环境中验证了 IDx 自主糖尿病视网膜病变（DR）筛查程序。该研究发现，对于可转诊 DR，该程序具有很高的敏感性（100%）但特异性较低（82%）。由此产生的阳性预测值为 19%，这意味着五名无可转诊 DR 的患者中，会有四人转诊至眼科，这将给眼科医生、初级保健诊所和患者带来巨大负担。与简单的转诊/不转诊输出相比，提供更好特异性、多个 DR 级别和病变在视网膜中位置注释的人工智能程序可能效果更好。这将通过让患者参与到困难的治疗建议中，更好地控制他们的糖尿病，从而改善医患关系。
