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

Abstract

Purpose: 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).

Methods: 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.

Results: 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.

Conclusions: 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.