Mathematical Models for Predicting Postoperative Axial length in Children With Bilateral Cataract and Primary Intraocular Lens Implantation: Toward Improved Pediatric Intraocular Lens Power Selection.

Abstract

Develop and compare predictive accuracy of two mathematical models: the logarithmic model and generalized estimating equation (GEE) model for estimating postoperative axial length (AL) in children following bilateral cataract surgery with primary intraocular lens (IOL) implantation, aiming to enhance IOL power selection. Comparison of mathematical prediction models. Eyes of children who underwent bilateral cataract surgery between January 2011 and December 2021 were included in the analysis. Data were only included if AL measurements were available preoperatively and at least 6 months postoperatively. The logarithmic and GEE models were developed and evaluated based on baseline AL (AL₀) and age at operation (age₀). Model performance was assessed using R² values, Lin's concordance correlation coefficients (CCC), and Bland-Altman analysis. One hundred one eyes (45 female, 56 male) with 401 postoperative AL measurements (median: 4/eye) were included. The derived logarithmic model was: AL = AL₀ + 2.87 × log₁₀ (age/age₀), yielding an R² of 0.8611 and a Lin's coefficient of 0.9149. The GEE model was: AL = -1.89 + 1.09 × AL₀ + 2.65 × log₁₀ (age) - 3.17 × log₁₀ (age₀) + 0.52 × (log₁₀ age₀ × log₁₀ age), showing an R² of 0.8682 and a Lin's coefficient of 0.9275. Predictions falling outside the 95% confidence interval were 7.5% for the logarithmic model and 7.7% for the GEE model. Both the logarithmic and GEE models demonstrated high reliability in predicting future AL based on baseline AL and age at surgery enhancing the accuracy of pediatric IOL power calculations.