RecruitingNot Applicable

Study on the Diagnostic Efficacy of ICL Selection and Prediction Depth Model Based on Eye Images

China326 participantsStarted 2021-01-02

Plain-language summary

To evaluate the diagnostic efficacy of deep learning network model in implantable collamer lens selection and prediction in a multicenter cross-sectional study

Who can participate

Age range18 Years – 45 Years

SexALL

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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion criteria

✓. Aged 18-45 years ;
✓. Myopia, with or without astigmatism, annual diopter change ≤ 0.50 D for 2 consecutive years ;
✓. Anterior chamber depth ≥ 2.80 mm ;
✓. Corneal endothelial cell count ≥ 2000 / mm2, stable cell morphology ;
✓. There were no other ocular diseases that significantly affected vision and / or systemic organic lesions that affected surgical recovery.

Exclusion criteria

✕. There were no other ocular diseases that significantly affected vision and / or systemic organic lesions that affected surgical recovery;
✕. Have a history of corneal refractive surgery or intraocular surgery ;
✕. Corneal endothelial cell count is low ;
✕. Those with systemic diseases ;
✕. Lactating or pregnant women.

What they're measuring

AUROC of convolutional neural network in predicting vault after ICL surgery

Timeframe: Day 7

AUROC of convolutional neural network in predicting anterior chamber angle after ICL implantation

Timeframe: Day 7

Trial details

NCT IDNCT06669728

SponsorSecond Affiliated Hospital of Nanchang University

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2027-08-31

Contact for this trial

Jian Xiong doctor

+8618170906556 894040417@qq.com

View on ClinicalTrials.gov More Posterior Chamber Phakic Intraocular Lens trials