Performance of Large Language Models for Structured Recognition and Refractive Prediction

NCT07183891 · tracked via the Priya Life Science China tracker

Sponsor

Jin Yang

Phase

Observational

Started

2025-08-01

Last updated

2025-09-19

Condition(s) studied

Cataract

Study summary

We conducted a single-center, retrospective observational study to evaluate large language models (ChatGPT 4o, GPT-5, DeepSeek) for automated interpretation of de-identified IOLMaster 700 reports provided as raster images. Models produced structured biometric extraction, toric IOL recommendation, and refractive predictions (sphere, cylinder, axis). Primary outcomes included parameter-level agreement and refractive error metrics; secondary outcomes included decision-support performance for toric IOL selection and agreement on ordered T-codes. No clinical intervention was performed.

Eligibility

Sex

ALL

Min age

18 Years

Max age

—

Healthy volunteers

Inclusion Criteria: -postoperative corrected distance visual acuity (CDVA) of 0.10 logMAR or better -an absolute IOL rotational stability of less than 10∘ at the 1-month follow-up examination Exclusion Criteria: * incomplete biometric data on the examination report; * a history of previous ocular surgery or ocular trauma * the occurrence of intraoperative complications, such as an anterior capsular tear or posterior capsular rupture * the development of significant postoperative complications, including but not limited to severe intraocular infection or inadequate pupillary dilation.

Primary outcome measure(s)

Refractive prediction error for sphere — At index examination
Mean absolute error (MAE, diopters) of model-predicted sphere versus clinical reference
Cohen's kappa with 95% CIs between model — At index examination (single time point)
Cohen's kappa with 95% CIs between model outputs and clinician-validated reference for per-parameter

Trial sites (1)

Facility	City	Region	Status
Eye and ENT hospital of Fudan University	Shanghai	Shanghai Municipality	Recruiting

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Official registry record

This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.

View NCT07183891 on ClinicalTrials.gov ↗ ← All trials in China