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

7. juli 2026 oppdatert av: Jian Xiong, Second Affiliated Hospital of Nanchang University

Efficacy of Deep Learning Models for Predicting Cycloplegic Refractive Error Based on Non-Cycloplegic Parameters in Adults With Myopia

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.

Studieoversikt

Detaljert beskrivelse

Myopia is a highly prevalent, irreversible refractive disorder with substantial impact on quality of life. Cycloplegic refraction is the gold standard for assessing refractive error in adults considering optical or surgical correction, but it is time-consuming, slow to recover from, and frequently associated with ocular discomfort. Non-cycloplegic refraction is therefore used routinely in clinical practice, despite known differences from cycloplegic values in a subset of adult myopes.

Critically, this discrepancy varies substantially between individuals and cannot be anticipated from non-cycloplegic measurements alone. Clinicians have no reliable way to identify, prior to dilation, which patients are likely to be overcorrected if cycloplegia is omitted, potentially leading to overcorrected prescriptions, asthenopia, and myopic progression.

Machine learning approaches that capture non-linear relationships between clinical predictors and refractive outcomes have shown promise in children, but comparable models for adults remain largely unexplored, and most rely on axial length, which is unavailable in routine optometric settings. Refractive surgery centers offer a uniquely suitable data source, as every candidate undergoes standardized paired non-cycloplegic and cycloplegic refraction with detailed anterior segment biometry during routine preoperative evaluation. This study leverages such data to develop and validate models estimating cycloplegic refractive error from non-cycloplegic parameters, providing a decision-support tool that reduces unnecessary cycloplegia while flagging patients for whom dilated refraction remains indicated.

Studietype

Observasjonsmessig

Registrering (Antatt)

2500

Kontakter og plasseringer

Denne delen inneholder kontaktinformasjon for de som utfører studien, og informasjon om hvor denne studien blir utført.

Studiekontakt

Studer Kontakt Backup

Studiesteder

      • Jiangxi, Kina
        • Rekruttering
        • The Second Affiliated Hospital of Nanchang University, Nanchang, JiangXi 330000
        • Ta kontakt med:
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Deltakelseskriterier

Forskere ser etter personer som passer til en bestemt beskrivelse, kalt kvalifikasjonskriterier. Noen eksempler på disse kriteriene er en persons generelle helsetilstand eller tidligere behandlinger.

Kvalifikasjonskriterier

Alder som er kvalifisert for studier

  • Voksen

Tar imot friske frivillige

Nei

Prøvetakingsmetode

Ikke-sannsynlighetsprøve

Studiepopulasjon

Each subject underwent a comprehensive preoperative examination, including cycloplegic and non-cycloplegic refractions, Pentacam, etc.

Beskrivelse

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.

Studieplan

Denne delen gir detaljer om studieplanen, inkludert hvordan studien er utformet og hva studien måler.

Hvordan er studiet utformet?

Designdetaljer

Kohorter og intervensjoner

Gruppe / Kohort
Intervensjon / Behandling
Group with spherical equivalent change ≥0.50 diopters after cycloplegic refraction
Adult myopes with a non-cycloplegic versus cycloplegic spherical equivalent difference of ≥0.50 diopters, for whom cycloplegic refraction is clinically warranted, received routine cycloplegic refraction with tropicamide; no other intervention was given.
The machine learning model was applied to each participant's non-cycloplegic parameters to predict cycloplegic spherical equivalent.
Group with spherical equivalent change <0.50 diopters after cycloplegic refraction
Adult myopes with an absolute difference of less than 0.50 diopters between non-cycloplegic and cycloplegic spherical equivalent, for whom non-cycloplegic refraction is considered sufficient, received routine cycloplegic refraction with tropicamide; no additional intervention was applied.
The machine learning model was applied to each participant's non-cycloplegic parameters to predict cycloplegic spherical equivalent.

Hva måler studien?

Primære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Accuracy of predicted cycloplegic spherical equivalent
Tidsramme: Day 0
Accuracy of the machine learning model in predicting cycloplegic spherical equivalent in the validation dataset, evaluated by mean absolute error, root mean square error, and coefficient of determination, expressed for spherical equivalent in diopters.
Day 0

Sekundære resultatmål

Resultatmål
Tiltaksbeskrivelse
Tidsramme
Diagnostic performance for identifying patients requiring cycloplegic refraction
Tidsramme: Day 0
Area under the receiver operating characteristic curve, sensitivity, and specificity of the model for classifying patients with an absolute difference of 0.50 diopters or more between non-cycloplegic and cycloplegic spherical equivalent in the validation dataset.
Day 0
Agreement between predicted and measured cycloplegic refraction
Tidsramme: Day 0
Agreement between predicted and measured cycloplegic spherical equivalent assessed by Bland-Altman analysis with mean bias and 95% limits of agreement, and by the intraclass correlation coefficient in the validation dataset.
Day 0

Samarbeidspartnere og etterforskere

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Studierekorddatoer

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Studer hoveddatoer

Studiestart (Faktiske)

3. oktober 2023

Primær fullføring (Antatt)

25. november 2026

Studiet fullført (Antatt)

25. november 2026

Datoer for studieregistrering

Først innsendt

21. juni 2026

Først innsendt som oppfylte QC-kriteriene

5. juli 2026

Først lagt ut (Faktiske)

8. juli 2026

Oppdateringer av studieposter

Sist oppdatering lagt ut (Faktiske)

9. juli 2026

Siste oppdatering sendt inn som oppfylte QC-kriteriene

7. juli 2026

Sist bekreftet

1. juli 2026

Mer informasjon

Begreper knyttet til denne studien

Ytterligere relevante MeSH-vilkår

Andre studie-ID-numre

  • [2026] NO.(123)

Plan for individuelle deltakerdata (IPD)

Planlegger du å dele individuelle deltakerdata (IPD)?

NEI

Legemiddel- og utstyrsinformasjon, studiedokumenter

Studerer et amerikansk FDA-regulert medikamentprodukt

Nei

Studerer et amerikansk FDA-regulert enhetsprodukt

Nei

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