Accuracy of a New Noninvasive Automatic Ocular Surface Analyzer for the Diagnosis of Dry Eye Disease-Two-Gate Design Using Healthy Controls.

Abstract

The purpose of this study was to assess the diagnostic performance of measurements from a new noninvasive, automated ocular surface analyzer (IDRA) in the diagnosis of dry eye disease (DED). We prospectively identified patients with and without DED using best practice methods. Subsequently, all participants underwent IDRA analysis, consisting of 5 components: noninvasive tear film break-up time, tear meniscus height, lipid layer interferometry, eye blink quality, and infrared meibography. The manufacturer provides cutoff values for a pathologic result for each of these components. Using a stepwise augmentation multivariate logistic regression model, we identified the components with the strongest association for the presence of DED. For the 3 components with the strongest association (interferometry, tear meniscus, and infrared meibography), we calculated the probability of DED. We enrolled 40 patients (80 eyes) with DED (mean age 60.5 years; women 78.3%) and 35 healthy subjects (70 eyes, mean age 31.1 years; women 21.7%). The IDRA had an area under the curve of 0.868 (95% confidence interval: 0.809-0.927) to detect DED. A normal (≥80) interferometry combined with a normal (>0.22) tear meniscus and a normal (≤40) infrared meibography was associated with an estimated probability of 18% for the presence of DED, whereas the estimated probability of DED was as high as 96% when all 3 findings were pathologic. The results of IDRA showed a positive concordance with routine clinical diagnostic tests. The new analyzer is an easy-to-access diagnostic tool to rule out the presence of DED in the extramural setting and to guide a timely DED treatment.