Department of Ophthalmology and Visual Sciences, 11205 PFP, University of Iowa Hospital and Clinics, 200 Hawkins Dr, Iowa City, IA 52242, USA.
JAMA Ophthalmol. 2013 Mar;131(3):351-7. doi: 10.1001/jamaophthalmol.2013.1743.
The diagnostic accuracy of computer detection programs has been reported to be comparable to that of specialists and expert readers, but no computer detection programs have been validated in an independent cohort using an internationally recognized diabetic retinopathy (DR) standard.
To determine the sensitivity and specificity of the Iowa Detection Program (IDP) to detect referable diabetic retinopathy (RDR).
In primary care DR clinics in France, from January 1, 2005, through December 31, 2010, patients were photographed consecutively, and retinal color images were graded for retinopathy severity according to the International Clinical Diabetic Retinopathy scale and macular edema by 3 masked independent retinal specialists and regraded with adjudication until consensus. The IDP analyzed the same images at a predetermined and fixed set point. We defined RDR as more than mild nonproliferative retinopathy and/or macular edema.
A total of 874 people with diabetes at risk for DR.
Sensitivity and specificity of the IDP to detect RDR, area under the receiver operating characteristic curve, sensitivity and specificity of the retinal specialists' readings, and mean interobserver difference (κ).
The RDR prevalence was 21.7% (95% CI, 19.0%-24.5%). The IDP sensitivity was 96.8% (95% CI, 94.4%-99.3%) and specificity was 59.4% (95% CI, 55.7%-63.0%), corresponding to 6 of 874 false-negative results (none met treatment criteria). The area under the receiver operating characteristic curve was 0.937 (95% CI, 0.916-0.959). Before adjudication and consensus, the sensitivity/specificity of the retinal specialists were 0.80/0.98, 0.71/1.00, and 0.91/0.95, and the mean intergrader κ was 0.822.
The IDP has high sensitivity and specificity to detect RDR. Computer analysis of retinal photographs for DR and automated detection of RDR can be implemented safely into the DR screening pipeline, potentially improving access to screening and health care productivity and reducing visual loss through early treatment.
计算机检测程序的诊断准确性已被报道与专家和有经验的读者相当,但没有任何计算机检测程序在使用国际公认的糖尿病视网膜病变(DR)标准的独立队列中得到验证。
确定爱荷华检测程序(IDP)检测可转诊性糖尿病视网膜病变(RDR)的敏感性和特异性。
在法国的初级保健 DR 诊所,从 2005 年 1 月 1 日至 2010 年 12 月 31 日,连续拍摄患者照片,并根据国际临床糖尿病视网膜病变量表和黄斑水肿对视网膜病变严重程度进行分级,由 3 位独立的有经验的视网膜专家进行分级,并进行裁决重新分级,直到达成共识。IDP 在预定的固定设定点分析相同的图像。我们将 RDR 定义为中度以上非增殖性视网膜病变和/或黄斑水肿。
共有 874 名有发生 DR 风险的糖尿病患者。
IDP 检测 RDR 的敏感性和特异性,接收者操作特征曲线下面积,视网膜专家读数的敏感性和特异性,以及平均观察者间差异(κ)。
RDR 的患病率为 21.7%(95% CI,19.0%-24.5%)。IDP 的敏感性为 96.8%(95% CI,94.4%-99.3%),特异性为 59.4%(95% CI,55.7%-63.0%),对应于 874 例假阴性结果中的 6 例(均不符合治疗标准)。接收者操作特征曲线下面积为 0.937(95% CI,0.916-0.959)。在裁决和达成共识之前,视网膜专家的敏感性/特异性分别为 0.80/0.98、0.71/1.00 和 0.91/0.95,平均分级者κ为 0.822。
IDP 对检测 RDR 具有较高的敏感性和特异性。DR 的视网膜照片计算机分析和 RDR 的自动检测可以安全地纳入 DR 筛查流程,这可能会提高筛查的可及性,提高医疗保健的效率,并通过早期治疗减少视力丧失。