A Prospective School-based Study of Myopia in Children in Southern China
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 4,000
- 试验地点
- 2
- 主要终点
- Incident myopia
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 6 Years 至 7 Years（Child）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •All first-grade students from 10 primary schools in urban counties, and from 10 primary schools in rural counties, Zhaoqing city.
排除标准
- 未提供
结局指标
主要结局
Incident myopia
时间窗: 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).
次要结局
- Prevalence of myopia(baseline)
- Area under the receiver operating characteristic curve of the deep learning algorithm for the prediction of fast progressing myope(1 year)
- Area under the receiver operating characteristic curve of the diagnostic algorithm in identifying abnormal vision screening result(baseline)
- Change in axial length(1 year, 2 years, 3 years)
- Sensitivity and specificity of the deep learning algorithm for the prediction of fast progressing myope(1 year)
- Sensitivity and specificity of the diagnostic algorithm in identifying abnormal vision screening result(baseline)
- Area under the receiver operating characteristic curve of the deep learning algorithm for the prediction of incident myopia(1 year)
- Prevalence of amblyopia, strabismus and other ocular abnormalities(baseline)
- Sensitivity and specificity of the deep learning algorithm for the prediction of incident myopia(1 year)
- Post-vision screening referral uptake(3 months)
研究者
Yingfeng Zheng
Clinical investigator
Sun Yat-sen University