School of Biomedicine, University of Manchester, United Kingdom.
Invest Ophthalmol Vis Sci. 2013 Jan 28;54(1):756-61. doi: 10.1167/iovs.12-10468.
To explore the diagnostic performance of threshold visual field tests using subsets of the standard 24-2 test pattern in detecting early/moderate glaucomatous field loss.
Normal (Brusini stage 0, n = 2344) and defective eyes (Brusini stage 2-3, n = 2222) from a database of visual field tests (6696 eyes/3586 patients, SITA standard 24-2 algorithm) were selected and resampled using a bootstrap method. The positive predictive values (PPVs) of each test location were calculated for the resampled datasets with a fail criteria of a single missed stimulus at a pattern deviation probability level of less than 0.01. Optimized test patterns started with the most frequent location of the maximum PPV in datasets. Eyes missing the location were removed and the PPV values of residual sample recalculated. The process was repeated until all defective eyes were detected. Receiver operating characteristic (ROC) curves were established for the PPV-optimized and five randomized patterns. Characteristics of visual field defects detected with subsets of optimized test pattern were established.
With the PPV-optimized pattern, 95% of the field defects were detected with 30 locations and all with 43 locations. Areas under the ROC curve were greatest for the optimized pattern. With each increment in the number of test locations, the Mean Deviation of additionally detected eyes became more positive while Pattern Standard Deviation became less positive (P < 0.001).
Good diagnostic performance can be obtained with optimized subsets of the standard 24-2 test pattern that can provide substantial savings in test times.
探索使用标准 24-2 测试模式子集进行阈值视野测试在检测早期/中度青光眼视野损失方面的诊断性能。
从视野测试数据库(6696 只眼/3586 例患者,SITA 标准 24-2 算法)中选择正常(Brusini 0 期,n=2344 只眼)和有缺陷的眼睛(Brusini 2-3 期,n=2222 只眼),并使用 bootstrap 方法进行重新抽样。对于具有失败标准(单个刺激缺失,模式偏差概率水平小于 0.01)的重新抽样数据集,计算每个测试位置的阳性预测值(PPV)。优化的测试模式从数据集的最大 PPV 最频繁的位置开始。缺失该位置的眼睛被移除,重新计算剩余样本的 PPV 值。重复此过程,直到检测到所有有缺陷的眼睛。为 PPV 优化的模式和五个随机模式建立了接收者操作特征(ROC)曲线。确定了使用优化测试模式子集检测到的视野缺陷的特征。
使用 PPV 优化的模式,95%的视野缺陷可以用 30 个位置检测到,而所有缺陷可以用 43 个位置检测到。ROC 曲线下的面积对于优化的模式最大。随着测试位置数量的增加,额外检测到的眼睛的平均偏差变得更加正向,而模式标准差变得更加负向(P<0.001)。
可以使用标准 24-2 测试模式的优化子集获得良好的诊断性能,从而大大节省测试时间。