SynthesisBMC ophthalmology2025
Network meta-analysis of intraocular lens power calculation formulas based on artificial intelligence in short eyes.
Synthesis in BMC ophthalmology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Evaluation of Intraocular Lens Power Calculation Formulas for Highly Myopic Eyes: A Systematic Review and Network Meta-Analysis.Journal of clinical medicine · 2026Review
- Comparative Analysis of Twenty Intraocular Lens Power Calculation Formulas in Medium-Long Eyes.Diagnostics (Basel, Switzerland) · 2026Article
- [Calculating IOL power - principles, development and current challenges].Die Ophthalmologie · 2026Review
- Advances in cataract surgery: is a new era on the horizon?Current opinion in ophthalmology · 2026Review
- Influence of Ocular Biometric Parameters on IOL Power Calculation Accuracy in Short and Normal Axial Length Eyes.Ophthalmology and therapy · 2026Article
- Comparisons of Intraocular Lens Calculation Formulas for Eyes With Astigmatism: Systemic Review and Network Meta-Analysis.Journal of ophthalmology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
purposeTo systematically assess and compare the accuracy of artificial intelligence (AI) -based intraocular lens (IOL) power calculation formulas with traditional IOL formulas in patients with short eye length.
designA systematic review and network meta-analysis.
methodsWe performed an exhaustive search of the PubMed, Embase, Web of Science, and Cochrane Library databases to identify relevant studies published until February 2024. The extracted data comprised the mean absolute error (MAE) and the percentage of eyes with refractive prediction errors (PE) within ± 0.50 and ± 1.00 diopters (D). Network meta-analysis was performed using Review Manager 5.3 and StataSE 16.0.
resultsA network meta-analysis of 21 formulas was carried out in 10 studies, including 756 eyes with axial length (AL) < 22 mm. The results showed that the top AI-based formula was Pearl-DGS. For the percentage of eyes with PE within ± 0.50 D, the Pearl-DGS formula demonstrated the highest accuracy. In terms of the percentage of eyes with PE within ± 1.00 D, the FullMonte IOL formula performed poorly, and no significant differences were observed among the other formulas.
conclusionsThe Pearl-DGS formula emerged as the leading AI-based method for determining IOL power in patients with short eye lengths, demonstrating superior accuracy compared to conventional vergence formulas.
Indexed as
Identifiers
What OpenQuestion holds
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.