Bühren J, Kook D, Kohnen T
Klinik für Augenheilkunde, Johann Wolfgang Goethe-Universität, Theodor-Stern-Kai 7, 60590, Frankfurt am Main, Deutschland.
Ophthalmologe. 2012 Jan;109(1):37-44. doi: 10.1007/s00347-011-2446-2.
For the detection of early stages of keratoconus (KC) several metrics have been developed in recent years. The aim of the study was to assess the suitability of keratometric indices to discriminate between eyes with early and subclinical KC from normal eyes.
From 33 eyes with early KC (group 1), 16 eyes with subclinical KC (group 2) und 121 normal eyes (group 3) the following metrics were computed from axial keratometric data: central keratometry (cK), astigmatism (AST), paracentral inferior-superior keratometric difference (PISD), skew of the steepest axes index (SRAX), the KISA% index, a discriminant function from the KISA% parameters AST, cK, PISD and SRAX (DKISA), corneal C(3) (-1) and a discriminant function from corneal Zernike coefficients (1(st)-7(th) order, pupil diameter 6 mm). The discriminative ability of these metrics between KC and normal eyes was assessed using receiver operating characteristic (ROC) curves and measuring the area under the curve (A (z)ROC).
Applying the published criteria, the Rabinowitz-McDonnell test (cK and PISD) and KISA% lacked sensitivity. Adjustment of critical values using ROC curve analysis improved the discriminative ability. The PISD (A (z)ROC 1 versus 3: 1, 2 versus 3: 0.947) and C(3) (-1) (A (z)ROC 1 and 0.98, respectively) metrics were the two single parameters with the highest discriminative ability. By weighting KISA parameters and Zernike coefficients with discriminant analyses, 100% of group 1 eyes (DKISA) and 96.7% of group 2 eyes (DA) were correctly classified.
After lowering the critical values the keratometric indices yielded a high discriminative ability for the detection of early KC stages. However, the excellent classification rates for wavefront-based metrics were not achieved.
近年来已开发出多种指标用于圆锥角膜（KC）早期阶段的检测。本研究的目的是评估角膜曲率指数区分早期和亚临床KC眼与正常眼的适用性。
从33只早期KC眼（第1组）、16只亚临床KC眼（第2组）和121只正常眼（第3组）的轴向角膜曲率数据中计算以下指标：中央角膜曲率（cK）、散光（AST）、中央旁下-上角膜曲率差异（PISD）、最陡轴指数偏斜（SRAX）、KISA%指数、来自KISA%参数AST、cK、PISD和SRAX的判别函数（DKISA）、角膜C(3)(-1)以及来自角膜泽尼克系数（1阶-7阶，瞳孔直径6mm）的判别函数。使用受试者工作特征（ROC）曲线并测量曲线下面积（A(z)ROC）评估这些指标在KC眼和正常眼之间的判别能力。
应用已发表的标准，拉宾诺维茨-麦克唐奈测试（cK和PISD）和KISA%缺乏敏感性。使用ROC曲线分析调整临界值可提高判别能力。PISD（A(z)ROC 1与3：1，2与3：0.947）和C(3)(-1)（A(z)ROC分别为1和0.98）指标是判别能力最高的两个单一参数。通过判别分析对KISA参数和泽尼克系数进行加权，第1组100%的眼（DKISA）和第2组96.7%的眼（DA）被正确分类。
降低临界值后，角膜曲率指数对早期KC阶段的检测具有较高的判别能力。然而，基于波前的指标未达到优异的分类率。
