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一种新的生物力学青光眼因素,用于区分正常眼压青光眼眼和正常眼。

A new biomechanical glaucoma factor to discriminate normal eyes from normal pressure glaucoma eyes.

机构信息

Department of Ophthalmology, Medical Faculty Carl Gustav Carus, Technische Universität, Dresden, Germany.

Augenklinik Wittenbergplatz, Berlin, Germany.

出版信息

Acta Ophthalmol. 2019 Nov;97(7):e962-e967. doi: 10.1111/aos.14115. Epub 2019 Apr 24.

Abstract

BACKGROUND

To test the ability of the newly calculated Dresden biomechanical glaucoma factor (DBGF) based on dynamic corneal response (DCR) deformation and corneal thickness parameters, to discriminate between healthy and normal pressure glaucoma (NPG) eyes.

METHODS

Seventy healthy and 70 NPG patients of Caucasian origin were recruited for this multicentre cross-sectional pilot study, which included both eyes for analysis. Logistic regression analysis with generalized estimating equation (GEE) models to account for correlations between eyes and a threefold cross-validation were performed to determine the optimal combination of Corvis ST parameters in order to separate normal from NPG eyes.

RESULTS

The DBGF was calculated using 5 Corvis ST parameters, which showed the best discrimination power: deformation amplitude ratio progression, highest concavity time, pachymetry slope, the biomechanically corrected intraocular pressure and pachymetry. In a threefold cross-validation, the receiver operating characteristic (ROC) curve confirmed an area under the curve (AUC) of 0.814 with a sensitivity of 76% and a specificity of 77% using a logit cut-off value of a DBGF = 0.5.

CONCLUSION

The DBGF shows to be sensitive and specific to discriminate healthy from NPG eyes. Since diagnosis of NPG is often challenging, the DBGF may help with the differential diagnosis of NPG in daily clinical practice. Therefore, it might be considered as a new possible screening method for NPG.

摘要

背景

测试基于动态角膜响应(DCR)变形和角膜厚度参数计算的新的德累斯顿生物力学青光眼因子(DBGF)的能力,以区分健康眼和正常眼压青光眼(NPG)眼。

方法

这项多中心横断面研究纳入了 70 名白种人健康眼和 70 名 NPG 患者,每只眼都进行了分析。采用广义估计方程(GEE)模型进行逻辑回归分析,以考虑眼间相关性,并进行三重交叉验证,以确定 Corvis ST 参数的最佳组合,从而将正常眼与 NPG 眼分开。

结果

使用 5 个 Corvis ST 参数计算了 DBGF,其具有最佳的区分能力:变形幅度比进展、最高凹陷时间、角膜厚度斜率、生物力学校正眼压和角膜厚度。在三重交叉验证中,接收者操作特征(ROC)曲线证实,使用 DBGF=0.5 的对数截断值,曲线下面积(AUC)为 0.814,灵敏度为 76%,特异性为 77%。

结论

DBGF 可用于敏感和特异性地区分健康眼和 NPG 眼。由于 NPG 的诊断常常具有挑战性,因此 DBGF 可能有助于在日常临床实践中对 NPG 进行鉴别诊断。因此,它可以被认为是 NPG 的一种新的可能的筛查方法。

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