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Relation between upper and lower lids' meibomian gland morphology, tear film, and dry eye

机译:上下眼睑睑板腺形态,泪膜和干眼症之间的关系

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PURPOSE.: To analyze relations between upper lid (UL) and lower lid (LL) meibomian gland (MG) morphology and tear film and the MG criteria ability to predict dry eye. METHODS.: MG, lipid layer, and non-invasive break-up time (NIBUT) were evaluated of the OD of 20 randomly selected subjects (female = 10; median age = 44.5 years, interquartiles = 39.5 to 55 years). Subjects were grouped into nine Ocular Surface Disease Index (OSDI)- and 11 OSDI+ by the OSDI. Non-contact infrared meibography and image analysis were performed to evaluate MG loss, MG thickness, and MG bent angle. RESULTS.: MG loss (Pearson correlation; r = 0.647, p = 0.003) and MG bent angle (r = 0.489, p = 0.027) were significantly correlated between lids, but MG thickness was not (r = -0.059, p = 0.413). MG loss was significantly (t-test; p = 0.048) less in the UL (median = 26.9%; LL = 32.3%), thicker in the LL (p < 0.001) and were more bent in the LL (p = 0.001). MG loss was significantly correlated to lipid-layer thickness (r < -0.597, p < 0.003) and NIBUT (r < -0.453, p < 0.030), whereas MG thickness and bent angle of the UL only were related to NIBUT (r < -0.563, p < 0.018). Combining MG loss of both lids (linear regression analysis) resulted in the best predictive ability of OSDI± (area under the receiver operative characteristic curve = 0.929, p = 0.001). CONCLUSIONS.: MG scores between lids were significantly different but correlated. MG loss was significantly correlated to tear film characteristics including lipid layer thickness and stability. MG thickness and bent angle of the UL were related to NIBUT. The combination of both lids' MG loss showed best predictive ability of dry eye.
机译:目的:分析上睑(UL)和下睑(LL)睑板腺(MG)形态与泪膜之间的关系,以及MG预测干眼症的能力。方法:对20名随机选择的受试者的OD(女性= 10;中位年龄= 44.5岁,四分位数= 39.5至55岁)进行评估,评估其MG,脂质层和非侵入性破裂时间(NIBUT)。通过OSDI将受试者分为9种眼表疾病指数(OSDI)-和11种OSDI +。进行了非接触式红外热成像和图像分析,以评估MG的损失,MG的厚度和MG的弯曲角度。结果:盖之间的MG损失(皮尔森相关; r = 0.647,p = 0.003)和MG弯曲角度(r = 0.489,p = 0.027)显着相关,但MG厚度没有相关性(r = -0.059,p = 0.413 )。 MG的MG丢失显着减少(t检验; p = 0.048)(UL中位数= 26.9%; LL = 32.3%),LL较厚(p <0.001),LL较弯曲(p = 0.001) 。 MG丢失与脂质层厚度(r <-0.597,p <0.003)和NIBUT(r <-0.453,p <0.030)显着相关,而MG的厚度和UL的弯曲角度仅与NIBUT(r < -0.563,p <0.018)。合并两个眼睑的MG损失(线性回归分析)可得出OSDI±的最佳预测能力(接受者手术特征曲线下的面积= 0.929,p = 0.001)。结论:眼睑之间的MG得分显着不同但相关。 MG损失与泪膜特性(包括脂质层厚度和稳定性)显着相关。 UL的MG厚度和弯曲角度与NIBUT有关。两个眼睑的MG损失组合显示出最佳的干眼预测能力。

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