Clinical trial Recruiting at 1 site Observational Ages 18 to 47

Predicting cycloplegic refractive error in myopia using standard eye measurements

Official title: Efficacy of Machine Learning Models for Predicting Cycloplegic Refractive Error Based on Non-Cycloplegic Parameters in Adults With Myopia

Run by Second Affiliated Hospital of Nanchang University · NCT07690813 · Data updated 2026-11-12

Researchers are testing a machine learning model to see if non-cycloplegic eye measurements can accurately predict cycloplegic refraction in adults with myopia, potentially reducing the need for dilating drops.

Quick facts

Study typeObservational
Ages18 Years to 47 Years
SexAll
Enrollment2500 (estimated)
SponsorSecond Affiliated Hospital of Nanchang University
Academic / other
Locations1 site (Jiangxi)
StatusRecruiting
StartedOctober 3, 2023
Main results expectedNovember 25, 2026
Study endsNovember 25, 2026
Registry record updatedSeptember 21, 2026
Trial IDNCT07690813 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Adults aged 18–60 with myopia and mild astigmatism who are candidates for refractive evaluation and have complete paired non-cycloplegic and cycloplegic refraction data available.

Probably not a fit

Patients whose refractions are highly variable or outside the model's validated range may not gain accurate predictions and still require cycloplegia.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This observational study develops and validates a machine learning model that estimates cycloplegic refractive error from non-cycloplegic measurements in adult myopes. Data are drawn from preoperative evaluations at a refractive surgery center, where paired non-cycloplegic and cycloplegic refractions with detailed anterior segment biometry are available. The goal is to identify which patients can avoid cycloplegia while still receiving accurate prescriptions. The project addresses variability in cycloplegic-versus non-cycloplegic refraction among individuals and aims to enable safer, faster clinical decisions. The study leverages non-linear modeling approaches to improve prediction accuracy in adults, a relatively underexplored area compared with pediatric populations.

Why it matters

Potential benefit: If successful, the model could reduce reliance on cycloplegic drops, speeding visits and improving patient comfort while preserving prescription accuracy.

How similar studies have gone: Previous pediatric-focused models showed promise; adult-specific approaches using standard measurements are less well established but feasible.

Who can join: the full rules

Show full inclusion / exclusion criteria
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.

Where it's running

  • The Second Affiliated Hospital of Nanchang University, Nanchang, JiangXi 330000
    Jiangxi, China
    Recruiting

Study contacts

Similar studies

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How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.