Abstract
Congenital cataract is a lens opacification that disrupts normal visual development, requiring early surgical intervention to prevent amblyopia. In children, timely surgery, followed by optical correction and vision rehabilitation, is crucial for achieving binocular vision with foveal fixation. The recommended surgical timing is within 8 weeks for unilateral cases and by 4 months for bilateral cases to minimize long-term visual impairment. Despite advancements in intraocular lens (IOL) technology and ophthalmic microsurgery, accurate IOL power selection in pediatric patients remains a challenge due to axial length growth, biometric variability, and the reliance on formulas derived from adult models. These factors contribute to postoperative refractive errors, making proper formula selection essential in minimizing additional corrective interventions. Traditional third-generation formulas, such as the Sanders-Retzlaff-Kraff-T and Holladay 1, are commonly used in pediatric cases. However, recent studies suggest that Barrett Universal II offers greater accuracy in older children, owing to its advanced vergence-based algorithm and improved axial length prediction. Emerging formulas, including Hill-RBF 3.0 and Kane, show promise but require further validation in pediatric cohorts. Additionally, ocular growth dynamics must be accounted for when determining postoperative refractive targets. Younger children often require undercorrection to compensate for axial elongation, and biometric formulas must be chosen accordingly to optimize long-term outcomes. The lack of pediatric-specific formulas further complicates IOL selection, emphasizing the need for new models that integrate machine learning algorithms and growth prediction data.