Abstract
Purpose :
Object measures of symptoms of dry eye are difficult to measure without an expert evaluating the eye in a slit lamp real time. In this study we assess the ability for the Ora EyeCup Phone to consistently capture eye redness in a large patient population. To obtain variations in eye redness patients were exposed to Ora’s Controlled Adverse Environment (CAE) with images acquired in the CAE.
Methods :
A custom android application on the pixel 5 was used to capture nasal and temporal images from 600 subjects with dry eye disease. Images were captured 29 times during the study, each time collecting a nasal and temporal view of each eye. Images were automatically uploaded from the phones and automatically downloaded onto expert graders computers. Using a custom grading software, graders evaluated each eye with the images with the nasal and temporal images on the screen. If the image was too blurry, the eye was closed or did not reach a sufficient interpalpebral fissure height, or patients gaze was off from the target that eye at that timepoint was marked as ungradable. Some timepoints images did not make it to the grading program either from issues in the upload or image acquisition issues at that timepoint.
Results :
Grading of the images is currently still ongoing, but to date total of 133,396 images, or 66,698 sets of nasal and temporal images, have been evaluated by an expert grader. Of these sets only 970 or 1.45% were marked as ungradable. However, some images that were supposed to be acquired and graded did not make it to the graders for reasons listed above. This accounted for an additional 764 missing image sets or 1.15%.
Conclusions :
The very low percentage of ungradable sets of images indicates the Ora EyeCup phone provides consistent quality for measuring ocular redness during clinical trials.
This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.