Department of Glaucoma, Sarakshi Netralaya, Nagpur, Maharashtra, India.
Department of Retina, Sarakshi Netralaya, Nagpur, Maharashtra, India.
Indian J Ophthalmol. 2019 Jan;67(1):75-81. doi: 10.4103/ijo.IJO_678_18.
To determine the diagnostic accuracy of a linear discriminant function (LDF) based on macular ganglion cell complex (GCC), optic nerve head (ONH) and retinal nerve fibre layer (RNFL) for differentiating early primary open-angle glaucoma (POAG) from glaucoma suspects.
In this cross-sectional study, data from consecutive 127 glaucoma suspects and 74 early POAG eyes were analysed. Each patient underwent detailed ocular examination, standard automated perimetry, GCC and ONH and RNFL analysis. After adjusting for age, gender and signal strength using the analysis of covariance; Benjamin-Hochberg multiple testing correction was performed to detect truly significant parameters to calculate the LDF. Subsequently, diagnostic accuracy of GCC and ONH and RNFL were determined. The obtained LDF score was evaluated for diagnostic accuracy in another test set of 32 suspect and 19 glaucomatous eyes. Data were analysed with the R-3.2.1 (R Core Team 2015), analysis of variance, t-test, Chi-square test and receiver operating curve.
Among all GCC parameters, infero temporal had the best discriminating power and average RNFL thickness and vertical CDR among ONH and RNFL parameters. LDF scores for GCC had AUROC of 0.809 for a cut-off value 0.07, while scores for ONH and RNFL had AUROC of 0.903 for a cut-off value - 0.24. Analysis on combined parametric space resulted in avg RNFL thickness, vertical CDR, min GCC + IPL and superior GCC + IPL as key parameters. LDF scores obtained had AUROC of 0.924 for a cut-off value 0.1. The LDF was applied to a test set with an accuracy of 84.31%.
The LDF had a better accuracy than individual GCC and ONH and RNFL parameters and can be used for diagnosis of glaucoma.
确定基于黄斑神经节细胞复合体（GCC）、视神经头（ONH）和视网膜神经纤维层（RNFL）的线性判别函数（LDF）在区分早期原发性开角型青光眼（POAG）与青光眼疑似患者的诊断准确性。
在这项横断面研究中，分析了连续 127 例青光眼疑似患者和 74 例早期 POAG 眼的数据。每位患者均接受详细的眼部检查、标准自动视野检查、GCC 和 ONH 以及 RNFL 分析。在使用协方差分析调整年龄、性别和信号强度后；采用 Benjamin-Hochberg 多重检验校正法来检测真正显著的参数，以计算 LDF。随后，确定了 GCC 和 ONH 和 RNFL 的诊断准确性。在另一组 32 例疑似和 19 例青光眼眼中评估获得的 LDF 评分的诊断准确性。使用 R-3.2.1（R Core Team 2015）、方差分析、t 检验、卡方检验和接收者操作曲线对数据进行分析。
在所有 GCC 参数中，下颞侧具有最佳的区分能力，而在 ONH 和 RNFL 参数中，平均 RNFL 厚度和垂直 CDR 具有最佳的区分能力。对于截断值为 0.07 的 GCC 的 LDF 评分，AUROC 为 0.809；而对于截断值为-0.24 的 ONH 和 RNFL 的 LDF 评分，AUROC 为 0.903。在联合参数空间上的分析得出，平均 RNFL 厚度、垂直 CDR、最小 GCC+IPL 和上侧 GCC+IPL 是关键参数。截断值为 0.1 的 LDF 评分 AUROC 为 0.924。将 LDF 应用于测试集，准确率为 84.31%。
LDF 比单个 GCC 和 ONH 和 RNFL 参数具有更高的准确性，可用于青光眼的诊断。
