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Diagnostic Performance of a Novel Noninvasive Workup in the Setting of Dry Eye Disease
Journal of Ophthalmology ( IF 1.447 ) Pub Date : 2020-12-11 , DOI: 10.1155/2020/5804123
Luca Vigo; Marco Pellegrini; Federico Bernabei; Francesco Carones; Vincenzo Scorcia; Giuseppe Giannaccare

Purpose. To evaluate the diagnostic performance of a novel noninvasive automated workup employed for the diagnosis of dry eye disease (DED). Methods. One hundred patients with mild to moderate DED and 100 matched control subjects were enrolled in this cross-sectional study. Ocular surface examinations were carried out by means of IDRA Plus (SBM Sistemi, Turin, Italy), which allows the automated evaluation of noninvasive breakup time (NIBUT), lipid layer thickness (LLT), tear meniscus height (TMH), infrared meibography for the measurement of meibomian gland loss (MGL), and blinking analysis. Continuous variables were compared between patients with DED and controls by using the Mann–Whitney U test. The area under the curve (AUC) of receiver operating characteristic curves was calculated. The correlations between ocular surface parameters were evaluated with Pearson correlation analysis. Results. Patients with DED showed significantly lower values of NIBUT, LLT, and TMH compared to controls (6.9 ± 2.5 vs 10.4 ± 2.4 s,  < 0.001; 64.6 ± 20.3 vs 73.4 ± 21.9 nm,  = 0.003; 0.231 ± 0.115 vs 0.289 ± 0.164,  = 0.012, respectively). Conversely, no significant differences were observed for MGL and blinking analysis (both  > 0.05). NIBUT had the highest diagnostic power (AUC = 0.841, sensitivity = 0.89, and specificity = 0.69), followed by LLT (AUC = 0.621, sensitivity = 0.89, and specificity = 0.55), TMH (AUC = 0.606, sensitivity = 0.57, and specificity = 0.63), blink analysis (AUC = 0.533, sensitivity = 0.48, and specificity = 0.59), and MGL (AUC = 0.531, sensitivity = 0.54, and specificity = 0.48). In patients with DED, NIBUT showed a significant correlation with TMH (R = 0.347,  = 0.002) and blinking analysis (R = 0.356,  < 0.001), while blinking analysis was negatively correlated with MGL (R = −0.315,  = 0.008). Conclusions. The automated noninvasive workup validated in this study may be a useful tool for reaching a noninvasive diagnosis of DED with a good performance, especially for NIBUT.

中文翻译:

新型无创性检查对干眼病的诊断性能

目的。为了评估用于干眼病(DED)诊断的新型无创自动化检查的诊断性能。方法。这项横断面研究招募了100名轻度至中度DED患者和100名匹配的对照受试者。眼表检查是通过IDRA Plus(意大利都灵SBM Sistemi公司)进行的,它可以自动评估无创性破裂时间(NIBUT),脂质层厚度(LLT),泪液半月板高度(TMH),红外热像仪测量睑板腺损失(MGL)和闪烁分析。使用Mann-Whitney U比较了DED患者和对照组的连续变量测试。计算接收器工作特性曲线的曲线下面积(AUC)。眼表参数之间的相关性通过Pearson相关分析进行评估。结果。与对照组相比,DED患者的NIBUT,LLT和TMH值显着降低(6.9±2.5 vs 10.4±2.4 s, <0.001; 64.6±20.3 vs 73.4±21.9 nm, = 0.003; 0.231±0.115 vs 0.289±0.164, 分别为0.012)。相反,MGL和眨眼分析均未观察到明显差异(两者均 > 0.05)。NIBUT具有最高的诊断能力(AUC = 0.841,敏感性= 0.89,特异性= 0.69),其次是LLT(AUC = 0.621,敏感性= 0.89,特异性= 0.55),TMH(AUC = 0.606,敏感性= 0.57,和特异性= 0.63),眨眼分析(AUC = 0.533,敏感性= 0.48,特异性= 0.59)和MGL(AUC = 0.531,敏感性= 0.54,特异性= 0.48)。在DED患者中,NIBUT与TMH显着相关(R  = 0.347, = 0.002)和眨眼分析(R  = 0.356, <0.001),而眨眼分析与MGL呈负相关(R  = -0.315, = 0.008)。结论。这项研究中验证的自动化无创检查可能是一种有用的工具,可对具有良好性能的DED进行无创诊断,尤其是对于NIBUT。
更新日期:2020-12-11
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