DL Models Predicting Cycloplegic Refractive Error Based on Non-Cycloplegic Parameters in Myopic Adults
Efficacy of Deep Learning Models for Predicting Cycloplegic Refractive Error Based on Non-Cycloplegic Parameters in Adults With Myopia
Panoramica dello studio
Stato
Condizioni
Intervento / Trattamento
Descrizione dettagliata
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.
Tipo di studio
Iscrizione (Stimato)
Contatti e Sedi
Contatto studio
- Nome: Jian Xiong
- Numero di telefono: 18170906556
- Email: 894040417@qq.com
Backup dei contatti dello studio
- Nome: Fu Gui
- Numero di telefono: 1387910191
- Email: 564436578@qq.com
Luoghi di studio
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Jiangxi, Cina
- Reclutamento
- The Second Affiliated Hospital of Nanchang University, Nanchang, JiangXi 330000
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Contatto:
- Jian Xiong
- Numero di telefono: 18170906556
- Email: 894040417@qq.com
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Contatto:
- Fu Gui
- Numero di telefono: 13879101919
- Email: 564436578@qq.com
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Criteri di partecipazione
Criteri di ammissibilità
Età idonea allo studio
- Adulto
Accetta volontari sani
Metodo di campionamento
Popolazione di studio
Descrizione
Inclusion Criteria:
- Age 18 to 60 years, of either sex;
- 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;
- Best-corrected visual acuity of 20/25 or better in each eye;
- Clear cornea, no keratoconus, corneal scarring, or other pathologies; clear lens;
- Intraocular pressure of 21 mmHg or less, with no history of glaucoma;
- No history of ocular surgery, especially corneal refractive surgery or cataract surgery;
- Time interval between non-cycloplegic refraction and cycloplegic refraction of 7 days or less, with complete data.
Exclusion Criteria:
- Incomplete clinical data to support the diagnosis;
- Ocular conditions such as subclinical keratoconus, keratoconus, or moderate-to-severe corneal haze or leukoma;
- Allergy or contraindication to cycloplegic agents;
- Refusal to participate in the study.
Piano di studio
Come è strutturato lo studio?
Dettagli di progettazione
Coorti e interventi
Gruppo / Coorte |
Intervento / Trattamento |
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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.
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The machine learning model was applied to each participant's non-cycloplegic parameters to predict cycloplegic spherical equivalent.
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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.
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The machine learning model was applied to each participant's non-cycloplegic parameters to predict cycloplegic spherical equivalent.
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Cosa sta misurando lo studio?
Misure di risultato primarie
Misura del risultato |
Misura Descrizione |
Lasso di tempo |
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Accuracy of predicted cycloplegic spherical equivalent
Lasso di tempo: Day 0
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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.
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Day 0
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Misure di risultato secondarie
Misura del risultato |
Misura Descrizione |
Lasso di tempo |
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Diagnostic performance for identifying patients requiring cycloplegic refraction
Lasso di tempo: Day 0
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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.
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Day 0
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Agreement between predicted and measured cycloplegic refraction
Lasso di tempo: Day 0
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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.
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Day 0
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Collaboratori e investigatori
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Completamento primario (Stimato)
Completamento dello studio (Stimato)
Date di iscrizione allo studio
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Primo inviato che soddisfa i criteri di controllo qualità
Primo Inserito (Effettivo)
Aggiornamenti dei record di studio
Ultimo aggiornamento pubblicato (Effettivo)
Ultimo aggiornamento inviato che soddisfa i criteri QC
Ultimo verificato
Maggiori informazioni
Termini relativi a questo studio
Parole chiave
Termini MeSH pertinenti aggiuntivi
Altri numeri di identificazione dello studio
- [2026] NO.(123)
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