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ML Models Predicting Cycloplegic Refractive Error Based on Non-Cycloplegic Parameters in Myopic Adults

Recruitingn/aAges 18 Years - 47 YearsAllSecond Affiliated Hospital of Nanchang University
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In plain words

What the trial is, and whether it could suit you

This study presents a machine learning model that predicts cycloplegic refraction in adults with myopia using standard non-cycloplegic eye measurements, aiming to reduce the need for cycloplegic drops while still identifying patients who require them.

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๐Ÿ“‹ Eligibility rules (as published)
Inclusion Criteria: 1. Age 18 to 60 years, of either sex; 2. Spherical equivalent between -0.50 diopters and -10.00 diopters, with myopia in one or both eyes, and with cylinder of 4.00 diopters or less; 3. Best-corrected visual acuity of 20/25 or better in each eye; 4. Clear cornea, no keratoconus, corneal scarring, or other pathologies; clear lens; 5. Intraocular pressure of 21 mmHg or less, with no history of glaucoma; 6. No history of ocular surgery, especially corneal refractive surgery or cataract surgery; 7. Time interval between non-cycloplegic refraction and cycloplegic refraction of 7 days or less, with complete data. Exclusion Criteria: 1. Incomplete clinical data to support the diagnosis; 2. Ocular conditions such as subclinical keratoconus, keratoconus, or moderate-to-severe corneal haze or leukoma; 3. Allergy or contraindication to cycloplegic agents; 4. Refusal to participate in the study.
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What it tests

  • Machine learning model for predicting cycloplegic refraction
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Where

1 site
The Second Affiliated Hospital of Nanchang University, Nanchang, JiangXi 330000
Jiangxi, China
๐Ÿค Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible โ€” always decide together with your own doctor.
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