The Discriminatory Ability of Ganglion Cell Inner Plexiform Layer Complex Thickness in Patients with Preperimetric Glaucoma

视网膜神经节细胞内丛状层复合体厚度对视野缺损前期青光眼患者的鉴别能力

阅读:1

Abstract

PURPOSE: To evaluate diagnostic performance of ganglion cell inner plexiform layer (GCIPL) and retinal nerve fiber layer (RNFL) parameters measured with Cirrus high-definition optical coherence tomography (OCT) in patients with preperimetric glaucoma. METHODS: In this multicenter cross-sectional study, 150 eyes of 83 patients with preperimetric glaucoma were compared with 200 eyes of age and sex matched healthy subjects. All patients had visual field testing and OCT scanning of GCIPL and RNFL in all quadrants. The independent Samples t-test was used to determine if a difference exists between the means of two independent groups on a continuous dependent variable. The area under the receiver operating characteristic (ROC) curve (AUC) of each parameter was calculated for discriminatory ability between normal controls and preperimetric glaucoma. The sensitivity and specificity were estimated by point coordinates on ROC curve. RESULTS: The best parameters for distinguishing preperimetric glaucoma from healthy eyes were the combined average GCIPL + average RNFL, followed by average RNFL + GCIPL (inferotemporal), and average RNFL + GCIPL (minimum). The GCIPL parameters with the highest to lowest AUC (in decreasing order) were inferotemporal, followed by average, minimum, superior, inferior, superonasal, inferonasal, superotemporal, and quadrants. The RNFL parameters with the highest to lowest AUC (in decreasing order) were average, followed by nasal, temporal, superior, and inferior quadrants. The sensitivity of combined GCIPL + RNFL parameters ranged 85%-88% and the specificity ranged 76%-88%. The sensitivity for RNFL parameters ranged 80%-90% and the specificity ranged 64%-88%. CONCLUSION: GCIPL and RNFL have good discriminatory ability; the sensitivity and specificity increase when both parameters are combined for early detection of glaucoma.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。