ArticleClinical ophthalmology (Auckland, N.Z.)2024
Revisiting the Visual Acuity Curves. A Proposed Methodology for the Evaluation of Postoperative Visual Acuity in Presbyopia.
Article in Clinical ophthalmology (Auckland, N.Z.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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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.
- Enhancing Postoperative Evaluation of Presbyopia Corrections: Correlation of Visual Curve Indices with Vision-Related Quality of Life.Journal of clinical medicine · 2025Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To identify the minimally required number of distances of visual acuity (VA) measurements for the reliable estimation of the visual acuity curve (VAC) and area of the curve (AoC) in presbyopia correction. Patients and Methods: The study was divided into a validation and a clinical phase with a total recruitment of 120 participants (120 eyes) who underwent uncomplicated pseudophakic presbyopia surgery with bilateral premium intraocular lenses (IOL) implantation. This study was conducted in the Department of Ophthalmology, University Hospital of Alexandroupolis, Alexandroupolis, Greece. Postoperative VAC and AoC were calculated with VA measurements taken at nine pre-defined distances. A mathematical model based on cubic spline interpolation was developed and assessed comparing the VAC and AoC values obtained using nine distances, with the ones predicted when a subset of VA measurements was inserted into the model. Results: Less than four measurements resulted in unreliable VAC and AoC assessment. Optimal distances for four to six VA measurements were determined. Mean error in the prediction of VAC and AoC of the clinical group ranged from 2.54 Letters/1.74% (6 measurements) to 2.90 letters/2.9% (4 measurements), respectively. Conclusion: Mathematical models that use cubic spline interpolation provide reliable VAC and AoC estimation, even with four VA measurements, when obtained at specific distances.
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