Telemedicine Evaluation of Dry Eye Disease Using a Portable Automatic Ocular Surface Imaging Device (PAOSID)
Telemedicine for Evaluating Dry Eye Disease (DED) Using a Mobile Phone-Attached Portable Automatic Ocular Surface Imaging Device (PAOSID): A Patient-Operated Diagnostic and Continuous Ocular Surface Monitoring (COSM) System
About This Trial
This study aims to evaluate the diagnostic accuracy and grading consistency of a mobile phone-attached portable automatic ocular surface imaging device (PAOSID) for assessing dry eye disease (DED). Both patients diagnosed with DED and healthy volunteers will undergo conventional clinical imaging, including white-light anterior segment photography, corneal fluorescein staining (CFS) under cobalt blue light, and tear film break-up time (TBUT), all performed under slit-lamp examination, as well as meibography. Clinical grading of DED severity will follow the TFOS DEWS I criteria, while other ocular surface findings-such as conjunctival injection, meibomian gland area loss, and CFS-will be assessed using standard ocular surface disease scoring scales. Following the clinical assessment, participants will use the PAOSID device to independently capture similar ocular surface images and videos. These remote images and videos will first be used to determine whether the participant has dry eye disease (DED). Regardless of the diagnosis result, all participants will undergo severity grading based on the TFOS DEWS I criteria, along with standardized scoring of ocular surface conditions such as conjunctival injection, meibomian gland area loss, and corneal fluorescein staining (CFS). The study will compare remote and clinical assessments to evaluate diagnostic agreement and grading consistency, and assess patient satisfaction and usability of the PAOSID system.
Who May Be Eligible (Plain English)
Original Eligibility Criteria
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Treatments Being Tested
DED diagnosis using PAOSID
A non-invasive diagnostic approach using the Portable Automatic Ocular Surface Imaging Device (PAOSID) to capture anterior segment images and videos for the assessment of dry eye disease (DED).
DED diagnosis using slit lamp
A non-invasive diagnostic approach using the slit lamp to capture anterior segment images and videos for the assessment of dry eye disease (DED).