Effect of Using Myopia Prediction Algorithm

NCT ID: NCT04005014

Last Updated: 2019-07-02

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

1680 participants

Study Classification

INTERVENTIONAL

Study Start Date

2019-07-08

Study Completion Date

2021-01-31

Brief Summary

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In this study, the investigators aim to perform a prospective, randomized controlled study to compare the myopia development between children using myopia prediction algorithm and children without using myopia prediction algorithm.

Detailed Description

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We propose to enroll Grade 3 children from primary schools in China. Children will be given examinations of visual acuity, eye refraction and biometrics, and be assigned to two groups: participants in group A use myopia prediction algorithm to predict myopia development, while in Group B, the participants do not use myopia prediction algorithm to predict myopia development. The visual acuity, eye refraction and biometrics will be investigated over the one-year follow-up period, aiming at comparison of actual myopia development between the two groups.

Conditions

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Eye--Refractive Errors

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

OTHER

Blinding Strategy

DOUBLE

Investigators Outcome Assessors
Examinations of visual acuity, eye refraction and biometrics will be performed in each participating clinic by trained investigators. The investigators, outcomes assessors involved in data management and analysis will be blinded to the group assignment. The study participants, the coordinator, senior consultants, and study personnel responsible for randomisation will not be masked.

Study Groups

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Using myopia prediction algorithm

After examination of visual acuity, eye refraction and biometrics, the examination results are shown to the children. Meanwhile, myopia prediction algorithm will be used to predict SE and presence of high myopia in the subsequent 10 years.

Group Type EXPERIMENTAL

Myopia prediction algorithm

Intervention Type OTHER

Candidate predictors included age at examination, SE, and annual progression rate. Using these predictors, the algorithm will be used to predict SE and whether patients will progress to high myopia in the subsequent 10 years.

Not using myopia prediction algorithm

After examination of visual acuity, eye refraction and biometrics, the examination results are shown to the children.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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Myopia prediction algorithm

Candidate predictors included age at examination, SE, and annual progression rate. Using these predictors, the algorithm will be used to predict SE and whether patients will progress to high myopia in the subsequent 10 years.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Children at Grade 3 (aged 8-9)
* Has the record of eye refraction examined in the past year
* Written informed consents provided

Exclusion Criteria

* Definitive diagnosis of other ocular abnormalities except for refractive error
* Previous eye surgery
* Unwilling to participate in this trial
Minimum Eligible Age

8 Years

Maximum Eligible Age

9 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Sun Yat-sen University

OTHER

Sponsor Role lead

Responsible Party

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Haotian Lin

Clinical Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Haotian Lin

Role: PRINCIPAL_INVESTIGATOR

Zhongshan Ophthalmic Center, Sun Yat-sen University

Central Contacts

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Yahan Yang

Role: CONTACT

+8615521013933

Haotian Lin

Role: CONTACT

+8613802793086

Other Identifiers

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CCPMOH2019-China-1

Identifier Type: -

Identifier Source: org_study_id

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