Comparing IOL refraction prediction accuracy and A-constant optimization for cataract surgery patients across South Indian and Midwestern United States populations

Comparing IOL refraction prediction accuracy and A-constant optimization for cataract surgery patients across South Indian and Midwestern United States populations

Abstract Background IOL power selection is a key determinant of refractive outcomes after cataract surgery. Numerous formulas exist to aid in this process; some are derived from geometric-optical principles (e.g., SRK/T, Barrett) while others are based on data-driven and machine learning approaches...

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Bibliographic Details
Main Authors: Omer Siddiqui, Elisa Warner, Miles Greenwald, Tingyang Li, Karthik Srinivasan, Aravind Haripriya, Nambi Nallasamy
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Ophthalmology
Subjects:
Cataract surgery
IOL
Refractive outcomes
Machine learning
Online Access:https://doi.org/10.1186/s12886-025-04217-2
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https://doi.org/10.1186/s12886-025-04217-2

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