Zhaoqing Myopia Study
- Conditions
- Myopia
- Interventions
- Diagnostic Test: Ophthalmic examinationsDevice: Wearable devices
- Registration Number
- NCT04219228
- Lead Sponsor
- Sun Yat-sen University
- Brief Summary
Myopia is a common cause of vision loss, being particularly prevalent in children in East and Southeast Asia. The investigators will assess prevalence and incidence of myopia, identify digital biomarkers associated with myopia, and validate algorithms for the detection and/or predition of myopia and other ocular abnormalities in school-aged children in both urban and rural settings in Southern China.
- Detailed Description
Myopia is a common cause of vision loss, being particularly prevalent in East and Southeast Asia. It is still not entirely clear whether and how visual experience in an urban environment with less outdoor exposure could have an impact on the development and progression of myopia. Zhaoqing has a relatively stable population of 4,084,600, which are representative of the Chinese population in term of demographic and socioeconomic characteristics.
Therefore, the investigators will conduct a longitudinal cohort study in both urban and rural settings to examine prevalence and incidence of myopia, identify digital biomarkers associated with myopia, and validate algorithms for the detection and/or predition of incidence and progression of myopia and other ocular abnormalities in school-aged children in Zhaoqing.
Recruitment & Eligibility
- Status
- UNKNOWN
- Sex
- All
- Target Recruitment
- 4000
- All first-grade students from 10 primary schools in urban counties, and from 10 primary schools in rural counties, Zhaoqing city.
- No.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Students in urban counties Ophthalmic examinations All first-grade students in urban counties will undergo anthropometry and ophthalmic examination, and be required to complete questionnaires and wear wearable devices to collect environmental information and daily activities. Students in urban counties Wearable devices All first-grade students in urban counties will undergo anthropometry and ophthalmic examination, and be required to complete questionnaires and wear wearable devices to collect environmental information and daily activities. Students in rural counties Ophthalmic examinations All first-grade students in rural counties will undergo anthropometry and ophthalmic examination, and be required to complete questionnaires and wear wearable devices to collect environmental information and daily activities. Students in rural counties Wearable devices All first-grade students in rural counties will undergo anthropometry and ophthalmic examination, and be required to complete questionnaires and wear wearable devices to collect environmental information and daily activities.
- Primary Outcome Measures
Name Time Method Incident myopia 3 years Incident myopia is defined as myopia detected during follow up among those without myopia at baseline. Myopia is defined as any eye's SER (sphere + 1/2 cylinder) of at least -0.5 diopters (D).
- Secondary Outcome Measures
Name Time Method Area under the receiver operating characteristic curve of the deep learning algorithm for the prediction of incident myopia 1 year The investigators will estimate the area under the receiver operating characteristic curve of the deep learning algorithm for the prediction of incident myopia.
Post-vision screening referral uptake 3 months Any referral uptake will be confirmed by telephone follow-up.
Prevalence of myopia baseline Myopia is defined as any eye's SER (sphere + 1/2 cylinder) of at least -0.5 diopters (D).
Area under the receiver operating characteristic curve of the deep learning algorithm for the prediction of fast progressing myope 1 year The investigators will estimate the area under the receiver operating characteristic curve of the deep learning algorithm for the prediction of fast progressing myope (a change in SER of 0.75D or more per year).
Area under the receiver operating characteristic curve of the diagnostic algorithm in identifying abnormal vision screening result baseline The investigators will estimate the area under the receiver operating characteristic curve of the diagnostic algorithm in identifying abnormal vision screening result (e.g., abnormal eye lid, abnormal cornea, and strabismus detected with mobile devices).
Change in axial length 1 year, 2 years, 3 years Axial length will be measured with a non-contact optical device.
Sensitivity and specificity of the deep learning algorithm for the prediction of fast progressing myope 1 year The investigators will estimate the sensitivity and specificity of the deep learning algorithm for the prediction of fast progressing myope (a change in SER of 0.75D or more per year). Cycloplegic spherical refraction changes measured by an auto-refractometer will be used as the indicator of myopia progression.
Sensitivity and specificity of the diagnostic algorithm in identifying abnormal vision screening result baseline The investigators will estimate the sensitivity and specificity of the diagnostic algorithm in identifying abnormal vision screening result (e.g., abnormal eye lid, abnormal cornea, and strabismus detected with mobile devices).
Prevalence of amblyopia, strabismus and other ocular abnormalities baseline Cover-uncover tests will be performed to detect strabismus. Any ocular abnormalities, including corneal opacities, lens opacities, and retinal diseases will be recorded based on slit lamp, direct ophthalmoscopic and/or mobile phone video examination. Participants with an uncorrected visual acuity 6/7.5 or worse with undergo subjective refraction to identify amblyopia.
Sensitivity and specificity of the deep learning algorithm for the prediction of incident myopia 1 year The investigators will estimate sensitivity and specificity of the deep learning algorithm for the prediction of incident myopia.
Trial Locations
- Locations (2)
Schools
🇨🇳Zhaoqing, Guangdong, China
Zhognshan Ophthalmic Center, Sun Yat-sen University
🇨🇳Guangzhou, Guangdong, China