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Effect of a Myopia Prediction System on Myopia Prevention and Control
Sponsor: Zhongshan Ophthalmic Center, Sun Yat-sen University
Summary
The global rise in myopia, particularly among children and adolescents in China, underscores the inadequacy of current prevention strategies, indicating that conventional screening and education alone are insufficient to curb the prevalence. Integrating personalized myopia prediction into routine care may enhance risk awareness, promote proactive prevention, and improve adherence to medical advice, ultimately reducing the future burden of high myopia. A myopia prediction system based on artificial intelligence was previously developed, accurately predicting future high myopia risk using efficient, robust, and easily accessible predictive factors, including age, spherical equivalent, and the annual progression of spherical equivalent. This study aims to conduct a prospective, one-year, cluster randomized controlled clinical trial to investigate the effectiveness of this prediction system in preventing and controlling myopia in school-aged children.
Official title: Impact of Feedback Based on the Myopia Prediction System on High Myopia Risk and Consultation Behavior in School-aged Children: a Cluster Randomized Controlled Trial
Key Details
Gender
All
Age Range
9 Years - 11 Years
Study Type
INTERVENTIONAL
Enrollment
20000
Start Date
2024-11-01
Completion Date
2026-02-28
Last Updated
2024-10-15
Healthy Volunteers
Yes
Interventions
Feedback on Predicted High Myopia Risk at Age 18 Using the Myopia Prediction System
At baseline and six months, participants will be provided with the results of their predicted risk of high myopia at age 18 based on the myopia prediction system.
Feedback on Ophthalmic Examinations
At baseline and six months, participants will be provided with the results of their ophthalmic examinations.
Locations (1)
Zhongshan Ophthalmic Center, Sun Yat-sen University
Guangzhou, Guangdong, China