ReviewClinical ophthalmology (Auckland, N.Z.)2026
Predictive Accuracy of Intraocular Lens Power Calculation Formulas for Cataract Surgery in Keratoconus: A Systematic Review and Network Meta-Analysis.
Review in Clinical ophthalmology (Auckland, N.Z.), 2026. 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
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
1 citing paper in PubMed.
- Predictive Accuracy of Intraocular Lens Power Calculation Formulas for Cataract Surgery in Keratoconus: A Systematic Review and Network Meta-Analysis [Letter].Clinical ophthalmology (Auckland, N.Z.) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Keratoconus (KCN) alters corneal curvature, complicating intraocular lens (IOL) power calculations for cataract surgery and increasing the risk of refractive errors. Traditional IOL formulas, designed for normal corneas, often yield suboptimal results, necessitating the evaluation of keratoconus-specific formulas. Objective: This study compares the predictive accuracy of IOL power calculation formulas in KCN patients undergoing cataract surgery, focusing on mean prediction error (MPE), mean absolute error (MAE), and the proportion of eyes achieving refractions within ±0.50 D and ±1.00 D. Methods: A systematic search of MEDLINE, Embase, and Cochrane databases identified seven studies (530 eyes). A Bayesian network meta-analysis (NMA) ranked formulas, including Barrett True-K (measured/predicted), Kane Keratoconus, Barrett Universal II, SRK/T, Holladay 1 and 2, Haigis, Higgins, and Hoffer Q. Subgroup analyses classified KCN severity using Amsler-Krumeich criteria. Results: Barrett True-K Measured and Kane Keratoconus demonstrated the highest predictive accuracy and consistently ranked among the best-performing formulas overall. Barrett True-K Predicted showed favorable performance in mild keratoconus, whereas SRK/T performed comparatively well in moderate disease. Conventional formulas, particularly Hoffer Q and Holladay formulas, showed lower predictive accuracy, especially in more advanced keratoconus. Overall, Barrett True-K and Kane Keratoconus achieved the highest proportions of eyes within ±0.50 D and ±1.00 D of target refraction. Conclusion: Barrett True-K and Kane Keratoconus demonstrated superior accuracy, while traditional formulas underperformed, especially in severe KCN. Keratoconus-specific formulas should be prioritized. The ranking probabilities of the including formulas are exploratory and should be interpreted cautiously due to limited and heterogeneous data. Future research should include larger sample sizes and standardized biometry for improved clinical decision-making.
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.