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Characteristics and Risk Factors Associated With Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application.

ABSTRACT: Importance:The incidence of dry eye disease has increased; the potential for crowdsource data to help identify undiagnosed dry eye in symptomatic individuals remains unknown. Objective:To assess the characteristics and risk factors associated with diagnosed and undiagnosed symptomatic dry eye using the smartphone app DryEyeRhythm. Design, Setting, and Participants:A cross-sectional study using crowdsourced data was conducted including individuals in Japan who downloaded DryEyeRhythm and completed the entire questionnaire; duplicate users were excluded. DryEyeRhythm was released on November 2, 2016; the study was conducted from November 2, 2016, to January 12, 2018. Exposures:DryEyeRhythm data were collected on demographics, medical history, lifestyle, subjective symptoms, and disease-specific symptoms, using the Ocular Surface Disease Index (100-point scale; scores 0-12 indicate normal, healthy eyes; 13-22, mild dry eye; 23-32, moderate dry eye; 33-100, severe dry eye symptoms), and the Zung Self-Rating Depression Scale (total of 20 items, total score ranging from 20-80, with ?40 highly suggestive of depression). Main Outcomes and Measures:Multivariate-adjusted logistic regression analysis was used to identify risk factors for symptomatic dry eye and to identify risk factors for undiagnosed symptomatic dry eye. Results:A total of 21?394 records were identified in our database; 4454 users, included 899 participants (27.3%) with diagnosed and 2395 participants (72.7%) with undiagnosed symptomatic dry eye, completed all questionnaires and their data were analyzed. A total of 2972 participants (66.7%) were women; mean (SD) age was 27.9 (12.6) years. The identified risk factors for symptomatic vs no symptomatic dry eye included younger age (odds ratio [OR], 0.99; 95% CI, 0.987-0.999, P?=?.02), female sex (OR, 1.99; 95% CI, 1.61-2.46; P?

SUBMITTER: Inomata T

PROVIDER: S-EPMC6902113 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Characteristics and Risk Factors Associated With Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application.

Inomata Takenori T Iwagami Masao M Nakamura Masahiro M Shiang Tina T Yoshimura Yusuke Y Fujimoto Keiichi K Okumura Yuichi Y Eguchi Atsuko A Iwata Nanami N Miura Maria M Hori Satoshi S Hiratsuka Yoshimune Y Uchino Miki M Tsubota Kazuo K Dana Reza R Murakami Akira A

JAMA ophthalmology 20200101 1

<h4>Importance</h4>The incidence of dry eye disease has increased; the potential for crowdsource data to help identify undiagnosed dry eye in symptomatic individuals remains unknown.<h4>Objective</h4>To assess the characteristics and risk factors associated with diagnosed and undiagnosed symptomatic dry eye using the smartphone app DryEyeRhythm.<h4>Design, setting, and participants</h4>A cross-sectional study using crowdsourced data was conducted including individuals in Japan who downloaded Dry ...[more]

PMID: 31774457

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Project description:BackgroundDry eye (DE) is a chronic inflammatory disease of the ocular surface of the eye that affects millions of people throughout the world. Smartphone use as an effective health care tool has grown exponentially. The "Dry eye or not?" app was created to evaluate the prevalence of symptomatic DE, screen for its occurrence, and provide feedback to users with symptomatic DE throughout Thailand.ObjectiveThe purpose of this study was to compare the prevalence of symptomatic dry eye (DE), blink rate, maximum blink interval (MBI), and best spectacle-corrected visual acuity (BSCVA) between people with and without symptomatic DE and to identify risk factors for symptomatic DE in Thailand.MethodsThis cross-sectional study sourced data from the "Dry eye or not?" smartphone app between November 2019 and July 2020. This app collected demographic data, Ocular Surface Disease Index (OSDI) score, blink rate, MBI, BSCVA, and visual display terminal (VDT) use data. The criterion for symptomatic DE was OSDI score ≥13.ResultsThe prevalence of symptomatic DE among individuals using this smartphone app in Thailand was 85.8% (8131/9482), with the Northeastern region of Thailand having the highest prevalence, followed by the Northern region. Worse BSCVA (median 0.20, IQR 0.40; P=.02), increased blink rate (median 18, IQR 16; P<.001), reduced MBI (median 8.90, IQR 10.80; P<.001), female sex (adjusted OR 1.83; 95% CI 1.59-2.09; P<.001), more than 6 hours of VDT use (adjusted OR 1.59; 95% CI 1.15-2.19; P=.004), and lower than bachelor's degree (adjusted OR 1.30; 95% CI 1.03-1.64; P=.02) were significantly associated with symptomatic DE. An age over 50 years (adjusted OR 0.77; 95% CI 0.60-0.99) was significantly less associated with symptomatic DE (P=.04).ConclusionsThis smartphone DE app showed that the prevalence of symptomatic DE in Thailand was 85.8%. Signs and risk factors could be also evaluated with this smartphone DE app. Screening for DE by this app may allow for the development of strategic plans for health care systems in Thailand.

Dataset Information

Characteristics and Risk Factors Associated With Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application.

Publications

Characteristics and Risk Factors Associated With Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application.

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