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Observational Study
. 2022 Jul:25:19-25.
doi: 10.1016/j.jtos.2022.04.005. Epub 2022 Apr 25.

DryEyeRhythm: A reliable and valid smartphone application for the diagnosis assistance of dry eye

Affiliations
Observational Study

DryEyeRhythm: A reliable and valid smartphone application for the diagnosis assistance of dry eye

Yuichi Okumura et al. Ocul Surf. 2022 Jul.

Abstract

Purpose: Undiagnosed or inadequately treated dry eye disease (DED) decreases the quality of life. We aimed to investigate the reliability, validity, and feasibility of the DryEyeRhythm smartphone application (app) for the diagnosis assistance of DED.

Methods: This prospective, cross-sectional, observational, single-center study recruited 82 participants (42 with DED) aged ≥20 years (July 2020-May 2021). Patients with a history of eyelid disorder, ptosis, mental disease, Parkinson's disease, or any other disease affecting blinking were excluded. Participants underwent DED examinations, including the Japanese version of the Ocular Surface Disease Index (J-OSDI) and maximum blink interval (MBI). We analyzed their app-based J-OSDI and MBI results. Internal consistency reliability and concurrent validity were evaluated using Cronbach's alpha coefficients and Pearson's test, respectively. The discriminant validity of the app-based DED diagnosis was assessed by comparing the results of the clinical-based J-OSDI and MBI. The app feasibility and screening performance were evaluated using the precision rate and receiver operating characteristic curve analysis.

Results: The app-based J-OSDI showed good internal consistency (Cronbach's α = 0.874). The app-based J-OSDI and MBI were positively correlated with their clinical-based counterparts (r = 0.891 and r = 0.329, respectively). Discriminant validity of the app-based J-OSDI and MBI yielded significantly higher total scores for the DED cohort (8.6 ± 9.3 vs. 28.4 ± 14.9, P < 0.001; 19.0 ± 11.1 vs. 13.2 ± 9.3, P < 0.001). The app's positive and negative predictive values were 91.3% and 69.1%, respectively. The area under the curve (95% confidence interval) was 0.910 (0.846-0.973) with concurrent use of the app-based J-OSDI and MBI.

Conclusions: DryEyeRhythm app is a novel, non-invasive, reliable, and valid instrument for assessing DED.

Keywords: Dry eye; DryEyeRhythm; Maximum blink interval; Mobile health; Ocular Surface Disease Index; ResearchKit; Screening; Smartphone application.

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