Ng Jason S, Bearse Marcus A, Schneck Marilyn E, Barez Shirin, Adams Anthony J
Vision Science Program, School of Optometry, University of California at Berkeley, Berkeley, California 94720-2020, USA.
Invest Ophthalmol Vis Sci. 2008 Apr;49(4):1622-8. doi: 10.1167/iovs.07-1157.
To derive and validate a model for use in predicting local retinal areas in which nonproliferative diabetic retinopathy (NPDR) lesions will develop over a 3-year period, by using primarily the implicit time (IT) of the multifocal electroretinogram (mfERG).
Eighteen diabetic patients were examined at baseline and at three annual follow-ups. Ophthalmic examinations, including fundus photographs and mfERG testing, were performed at each visit. Thirty-five retinal zones were constructed from the 103-element stimulus array, and each zone was assigned the maximum IT z-score within it based on 30 age-similar control subjects. Logistic regression was used to investigate the development of retinopathy in relation to baseline mfERG IT delays and additional diabetic health variables. Receiver operating characteristic (ROC) curves were used to evaluate the models.
Retinopathy developed in 77 of the 1208 retinal zones, of which 25 had recurring retinopathy. Multivariate analyses yielded baseline mfERG IT, duration of diabetes, and blood glucose concentration as the most important predictors of recurring retinopathy. mfERG ITs were not predictive of transient retinopathy. ROC curves based on the multivariate model for the prediction of recurring retinopathy resulted in an area under the curve of 0.95, sensitivity of 88%, and specificity of 98%. Ten-fold cross-validation confirmed the high sensitivity and specificity of the model.
The development of recurring retinopathy over a 3-year period can be well predicted by using a multivariate model based on mfERG implicit time. Multifocal ERG delays are promising candidate measures for trials of novel therapeutics directed at preventing or slowing the progression of NPDR.
主要利用多焦视网膜电图（mfERG）的隐含时间（IT），推导并验证一个用于预测非增殖性糖尿病视网膜病变（NPDR）病变将在3年内发生的局部视网膜区域的模型。
18名糖尿病患者在基线时以及每年进行3次随访时接受检查。每次就诊时均进行眼科检查，包括眼底照相和mfERG测试。从103元素刺激阵列构建35个视网膜区域，并根据30名年龄相仿的对照受试者为每个区域分配其内部的最大IT z评分。使用逻辑回归研究视网膜病变的发生与基线mfERG IT延迟及其他糖尿病健康变量之间的关系。采用受试者操作特征（ROC）曲线评估模型。
在1208个视网膜区域中的77个出现了视网膜病变，其中25个有复发性视网膜病变。多变量分析得出基线mfERG IT、糖尿病病程和血糖浓度是复发性视网膜病变的最重要预测因素。mfERG IT不能预测短暂性视网膜病变。基于多变量模型预测复发性视网膜病变的ROC曲线下面积为0.95，敏感性为88%，特异性为98%。十折交叉验证证实了该模型的高敏感性和特异性。
使用基于mfERG隐含时间的多变量模型可以很好地预测3年内复发性视网膜病变的发生。多焦ERG延迟是针对预防或减缓NPDR进展的新型治疗试验的有前景的候选指标。
