ReviewMedicine2025
Intraocular lens power calculation in pediatric cataract surgery: A narrative review.
Review in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Neural Network-Based Prediction of Post-Operative Visual Outcomes Following Secondary Pediatric Intraocular Lens Implantation.Children (Basel, Switzerland) · 2025Article
- Innovations in Intraocular Lens Power Calculation-A Review.Journal of clinical medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.