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Defective angles of localized retinal nerve fiber layer reflect the severity of visual field defect- a cross-sectional analysis

机译:局部视网膜神经纤维层的缺陷角度反映了视野缺陷的严重程度 - 横截面分析

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摘要

Abstract Background In order to detect glaucomatous optic nerve damages early on and evaluate the severity of glaucoma, a previously developed analytic method based on photographic retinal nerve fiber layer (RNFL) angle defect was proposed. However, the correlation between these defective angles and the severity of visual field defect has not been verified. This study aimed to confirm the correlation described above. Methods We reviewed a total of 227 glaucomatous eyes (38 enrolled, 189 excluded) during an interval of 5 years. The angles of all eyes were measured on RNFL photograph, of which angle α is the angular width between the macula center and the proximity of RNFL defect, and angle β (+c) is the sum of angular width(s) of localized RNFL defect. The severity of visual field defect was determined by mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI). Correlation analysis was performed on angle α and angle β (+c) with the presence of central scotoma and visual field defect parameters, respectively. Results Angle β (+c) showed significant correlation with MD (P = 0.007), PSD (P = 0.02), VFI (P = 0.03), and average RNFL thickness (P = 0.03). No correlation was found between angle α and the presence of central scotoma. Conclusions In conclusion, measuring the angular width of localized RNFL defect is a viable method for determining the severity of visual field defect.
机译:摘要背景是早期检测青光眼视神经损伤,评价青光眼的严重程度,提出了一种基于摄影视网膜神经纤维层(RNFL)角缺陷的先前开发的分析方法。然而,尚未验证这些缺陷角度与视野缺陷的严重程度之间的相关性。本研究旨在确认上述相关性。方法在5年的时间间隔内,我们共审查了总共227名青光眼眼睛(38人,189名,排除在外)。在RNFL照片上测量所有眼睛的角度,其中角度α是MACULA中心和RNFL缺陷的接近度之间的角度宽度,并且角度β(+ C)是局部RNFL缺陷的角度宽度之和。通过平均偏差(MD),图案标准偏差(PSD)和视野索引(VFI)确定了视野缺陷的严重程度。对角度α和角度β(+ C)进行相关分析,分别存在中央速度和视野缺陷参数。结果角度β(+ C)显示出与MD(P = 0.007),PSD(P = 0.02),VFI(P = 0.03)和平均RNFL厚度(P = 0.03)相关的显着相关性。角度α与中央苏格兰的存在之间没有发现相关性。结论总之,测量局部RNFL缺陷的角度宽度是用于确定视野缺陷的严重程度的可行方法。

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