Myopia Clinical Trial
Official title:
A Prospective School-based Study of Myopia in Children in Southern China
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.
Status | Recruiting |
Enrollment | 4000 |
Est. completion date | February 2, 2023 |
Est. primary completion date | February 2, 2023 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 6 Years to 7 Years |
Eligibility |
Inclusion Criteria: - All first-grade students from 10 primary schools in urban counties, and from 10 primary schools in rural counties, Zhaoqing city. Exclusion Criteria: - No. |
Country | Name | City | State |
---|---|---|---|
China | Zhognshan Ophthalmic Center, Sun Yat-sen University | Guangzhou | Guangdong |
China | Schools | Zhaoqing | Guangdong |
Lead Sponsor | Collaborator |
---|---|
Sun Yat-sen University |
China,
He M, Zheng Y, Xiang F. Prevalence of myopia in urban and rural children in mainland China. Optom Vis Sci. 2009 Jan;86(1):40-4. doi: 10.1097/OPX.0b013e3181940719. — View Citation
Li SM, Liu LR, Li SY, Ji YZ, Fu J, Wang Y, Li H, Zhu BD, Yang Z, Li L, Chen W, Kang MT, Zhang FJ, Zhan SY, Wang NL, Mitchell P; Anyang Childhood Eye Study Group. Design, methodology and baseline data of a school-based cohort study in Central China: the An — View Citation
Morgan IG, Ohno-Matsui K, Saw SM. Myopia. Lancet. 2012 May 5;379(9827):1739-48. doi: 10.1016/S0140-6736(12)60272-4. Review. — View Citation
Negrel AD, Maul E, Pokharel GP, Zhao J, Ellwein LB. Refractive Error Study in Children: sampling and measurement methods for a multi-country survey. Am J Ophthalmol. 2000 Apr;129(4):421-6. — View Citation
Ojaimi E, Rose KA, Smith W, Morgan IG, Martin FJ, Mitchell P. Methods for a population-based study of myopia and other eye conditions in school children: the Sydney Myopia Study. Ophthalmic Epidemiol. 2005 Feb;12(1):59-69. — View Citation
Zadnik K, Mutti DO. Outdoor Activity Protects Against Childhood Myopia-Let the Sun Shine In. JAMA Pediatr. 2019 May 1;173(5):415-416. doi: 10.1001/jamapediatrics.2019.0278. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Incident myopia | 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). | 3 years | |
Secondary | Prevalence of myopia | Myopia is defined as any eye's SER (sphere + 1/2 cylinder) of at least -0.5 diopters (D). | baseline | |
Secondary | Change in axial length | Axial length will be measured with a non-contact optical device. | 1 year, 2 years, 3 years | |
Secondary | Prevalence of amblyopia, strabismus and other ocular abnormalities | 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. | baseline | |
Secondary | Area under the receiver operating characteristic curve of the deep learning algorithm for the prediction of incident myopia | The investigators will estimate the area under the receiver operating characteristic curve of the deep learning algorithm for the prediction of incident myopia. | 1 year | |
Secondary | Sensitivity and specificity of the deep learning algorithm for the prediction of incident myopia | The investigators will estimate sensitivity and specificity of the deep learning algorithm for the prediction of incident myopia. | 1 year | |
Secondary | Area under the receiver operating characteristic curve of the deep learning algorithm for the prediction of fast progressing myope | 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). | 1 year | |
Secondary | Sensitivity and specificity of the deep learning algorithm for the prediction of fast progressing myope | 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. | 1 year | |
Secondary | Area under the receiver operating characteristic curve of the diagnostic algorithm in identifying abnormal vision screening result | 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). | baseline | |
Secondary | Sensitivity and specificity of the diagnostic algorithm in identifying abnormal vision screening result | 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). | baseline | |
Secondary | Post-vision screening referral uptake | Any referral uptake will be confirmed by telephone follow-up. | 3 months |
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