Quantitative framework for synthesising defocus-curve evidence in simultaneous-vision intraocular lenses.

Authors

Maria Laura Passaro, Ferdinando Giuliano, Matilde Buzzi, Mariacarmela Ventura, Rita Mencucci, Ersilia Lucenteforte, Mor M Dickman, Gianni Virgili, Vito Romano

Published in

The British journal of ophthalmology. Sep 23, 2026. Epub Sep 23, 2026.

Abstract

To develop a quantitative, meta-analytic framework to synthesise defocus-curve evidence and describe functional visual performance of simultaneous vision intraocular lenses (SVIOLs) across clinically relevant visual ranges.
PubMed was searched from inception through June 2025 using predefined terms related to cataract surgery, intraocular lenses and defocus curves. Studies of cataract surgery or refractive lens exchange with capsular bag implantation of SVIOLs reporting postoperative defocus curves were included. Randomised and non-randomised studies, cohort studies and case series were eligible. Defocus-curve data were extracted from tables or digitised from figures and summarised within predefined ranges: far (+1.00 to -0.50 D), intermediate (-0.50 to -2.00 D) and near (-2.00 to -3.50 D). Random-effects meta-analyses were performed for each IOL model. Exploratory latent class analysis (LCA) and meta-regression assessed performance patterns and associations with patient-reported outcomes. Outcomes included mean logMAR visual acuity across visual ranges, data-driven clustering of IOL performance and association with spectacle independence.
A total of 125 studies including 18 077 eyes and 84 IOL models were analysed. Across IOL models, 97.1% achieved mean far acuity of 0.2 logMAR or better compared with 71.6% for intermediate and 67.5% for near. Considerable between-study heterogeneity was observed across all ranges. LCA identified four clusters reflecting a continuum from full-range to distance-dominant visual performance. Better near visual acuity was significantly associated with higher spectacle independence, explaining 45.2% of its variance.
Range-based descriptors enable reproducible comparison across heterogeneous studies and support evidence synthesis. This framework provides a practical approach to operationalise functional classification of SVIOLs and link visual performance to patient-reported outcomes.

PMID:
42778340
Bibliographic data and abstract were imported from PubMed on 24 Sep 2026.

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