Observational studyJournal of medicine and life2025
Does gender affect intraocular lens power calculations? A comparative analysis of formula accuracy.
Observational study in Journal of medicine and life, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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Who cites it
1 citing paper in PubMed.
- The Role of Sex in Ocular Biometry: A Large-Scale Study of Cataract Candidates in Greece.Ophthalmology and therapy · 2026Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Intraocular lens (IOL) power calculation is a crucial aspect of modern cataract surgery, directly affecting postoperative refractive outcomes. Due to anatomical and physiological differences between male and female eyes, neglecting gender-specific variations may lead to systematic refractive errors in IOL power selection. This research aimed to determine the necessity of incorporating gender as a variable in future IOL calculation algorithms to improve postoperative precision. This retrospective observational study analyzed data from 210 eyes that met predefined inclusion criteria. Biometric measurements for assessing intraocular lens power were obtained using the ARGOS optical biometer. The refractive power of the intraocular lenses was calculated using several established formulas, and these values were systematically compared to evaluate their predictive accuracy. A parametric statistical approach was employed, using repeated measures ANOVA to assess differences among multiple calculations. The homogeneity of covariances was examined to validate the design of the repeated measures. Pairwise comparisons of the outcomes from different formulas were performed using the Bonferroni correction to identify statistically significant differences. Additionally, paired-sample
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