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NCT Number: NCT06633393

Effect of a Myopia Prediction System on Myopia Prevention and Control

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.

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Key information

Conditions

Myopia Artificial Intelligence (AI) Eye Diseases Randomized Controlled Trials Refractive Errors

Age range

9 year–11 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Zhongshan Ophthalmic Center, Sun Yat-sen University

Guangzhou, Guangdong, China

Location contact

Haotian Lin, M.D., Ph.D

CONTACT

[email protected]

+86 13802793086

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • The participant and their guardian voluntarily signed the informed consent form
  • Has the record of eye refraction examination in the past year
  • Aged 9 to 11 years, regardless of gender

Exclusion criteria

  • High myopia(spherical equivalent ≤ -6.00 D)
  • Ocular diseases other than myopia (e.g., strabismus, amblyopia, congenital cataract, juvenile glaucoma, retinal diseases).
  • Systemic diseases that may affect vision or visual development (e.g., diabetes or other endocrine disorders, cardiovascular or respiratory diseases, Down syndrome)

Treatment and study plan

Feedback on Predicted High Myopia Risk at Age 18 Using the Myopia Prediction System

Other

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

Other

At baseline and six months, participants will be provided with the results of their ophthalmic examinations.

Primary outcomes

  1. Proportion of Individuals Predicted to Develop High Myopia at Age 18 by the Myopia Prediction System

    Time frame: 1 year

    At the end of the one-year study, the Myopia Prediction System will be used to predict whether students will develop high myopia at age 18 in both the intervention and control groups. The Proportion of Individuals Predicted to Develop High Myopia at Age 18 by the Myopia Prediction System is calculated as the total number of students in each group predicted to develop high myopia by age 18, divided by the total number of students in the respective group.

  2. Cumulative Clinical Visit Rate for Myopia Prevention and Control

    Time frame: Within 3 months after each intervention

    The Cumulative Clinical Visit Rate Proportion of Clinical Visits for Myopia Prevention and Control is the proportion of students in the intervention or control group who visited a hospital or clinic for myopia-related care (e.g., refractive exams and treatment) at least once within three months of either intervention. It is calculated as the number of students in each group who attended a clinical visit within three months of at least one intervention, divided by the total number of students in the respective group.

Secondary outcomes

  1. Myopia Incidence Rate

    Time frame: 1 year

    1-year myopia incidence rate = number of new myopia cases within one year / number of non-myopic cases at baseline * 100%

  2. Changes in Spherical Equivalent

    Time frame: 1 year

    Change in spherical equivalent (non-cycloplegic autorefraction) will be calculated

  3. Screen Time

    Time frame: 1 year

    Daily usage time of electronic devices (computer/smartphone/tablet computer) will be calculated

  4. Outdoor Activity Time

    Time frame: 1 year

    Daily outdoor activity time will be calculated

Study contacts

Contact information is provided by the study sponsor or research team.

Xinwei Chen, M.D.

CONTACT

[email protected]

+86 13535382011

Yahan Yang, M.D., Ph.D

CONTACT

[email protected]

+86 15521013933

Sponsors and collaborators

Lead sponsor

Zhongshan Ophthalmic Center, Sun Yat-sen University

Other

Registry information

Official study 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

Important dates

Study start
2024
Primary completion
2025
Study completion
2026
First posted
Oct 9, 2024
Registry last updated
Oct 15, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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