Bayes Statistics For Phakic Lens Diameter Prediction (Part Of The 5000 Eye Study)
Published 2023 - 41st Congress of the ESCRS
Reference: PP22.16 | Type: Free paper | DOI: 10.82333/5stb-qg51
Authors: Nino Hirnshall* 1 , Haidar Khalil 1 , Theresa Höftberger 1 , Peter Laubichler 1 , Matthias Bolz 1
1Ophthalmology,Kepler University CLinic and Johannes Kepler University,Linz,Austria
Purpose
Accurate prediction of the lens diameter could improve intraocular lens (IOL) power calculation significantly. Aim of this study was to use Bayesian statistics and a large data set to predict the lens diameter of the phakic eye.
Setting
Department of Ophthalmology and Optometry at the Kepler University Clinic Linz, Austria.
Methods
This epidemiological study included patient data collected between June 2020 and October 2022. Requested measurements were two different ss-OCT measurements (IOLMaster700 and Casia2) to investigate on axial eye length, anterior chamber depth, corneal radii, angle-to-angle distance and lens thickness and their influence on the size of the lens equator. Statistical analysis included a descriptive analysis as well as Bayesian statistics.
Results
In total, 5291 phakic eyes were included in this study. Mean lens diameter was 10.1 mm (SD: 0.6; median: 10.2; range: 6.8 – 12.0). Mean lens thickness was found to be 4.6 mm (SD: 0.4; median: 4.6; range: 2.2 – 6.9). Correlation between lens diameter and axial eye length (r=0.36), anterior chamber depth (r=0.24) and lens thickness (r=0.34) was found to be only moderate. A Bayesian approach to predict the lens diameter will be presented at the ESCRS meeting.
Conclusions
Bayesian statistics helps to predict the lens diameter, although correlation between different anatomical distances in the eye and the lens diameter was found to be only moderate. Predicting the lens diameter is a significant step to improve IOL power calculation.