June 2020
Volume 61, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2020
Predicting Refractive Outcomes after Cataract Surgery using Biometry-based Validation Criteria
Author Affiliations & Notes
  • Alexander Baten-Tschan
    Department of Ophthalmology, Penn State College of Medicine, Hershey, Pennsylvania, United States
  • Catherine Seeger
    Penn State College of Medicine, Pennsylvania, United States
  • Andrew Luo
    Penn State College of Medicine, Pennsylvania, United States
  • Brett Ernst
    Schein Ernst Mishra Eye, Harrisburg, Pennsylvania, United States
  • Ingrid U Scott
    Department of Ophthalmology, Penn State College of Medicine, Hershey, Pennsylvania, United States
    Department of Public Health Sciences, Penn State College of Medicine, Hershey, Pennsylvania, United States
  • Seth Pantanelli
    Department of Ophthalmology, Penn State College of Medicine, Hershey, Pennsylvania, United States
  • Footnotes
    Commercial Relationships   Alexander Baten-Tschan, None; Catherine Seeger, None; Andrew Luo, None; Brett Ernst, None; Ingrid Scott, None; Seth Pantanelli, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 593. doi:
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      Alexander Baten-Tschan, Catherine Seeger, Andrew Luo, Brett Ernst, Ingrid U Scott, Seth Pantanelli; Predicting Refractive Outcomes after Cataract Surgery using Biometry-based Validation Criteria. Invest. Ophthalmol. Vis. Sci. 2020;61(7):593.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Intraocular lens (IOL) power prediction formulas perform better in eyes with normal biometry compared to those with extreme biometric values. However, cataract surgery outcomes are often pooled and include eyes with highly variable axial lengths, anterior chamber depths, and keratometry values. The purpose of this study is to refine a previously constructed scoring rubric that stratifies eyes with normal and eccentric biometric values and determine whether it can differentiate eyes with an exceptionally high likelihood of a good refractive outcome from those without.

Methods : Retrospective consecutive case series of all eyes that underwent cataract surgery with implantation of a one-piece acrylic IOL (Bausch & Lomb Akreos AO60) between January 2016 and June 2018 by a single surgeon. Eyes were scored by five validation criteria, which established upper and lower boundaries for normal axial length (22.0-25.2 mm), keratometry (41-47 D), anterior chamber depth (2.75-3.75 mm), lens thickness (4.0-5.3 mm), and white-to-white (10.7-12.6 mm). One point was given for each criterion met. The refractive outcomes for eyes that scored the maximum 5 points were compared to those that did not meet all criteria (<5 points). Eyes with prior surgery, biometric measurements performed using immersion A-scan, lack of post-operative refraction, or a post-operative best-corrected visual acuity less than 20/40 were excluded from the analysis.

Results : 764 eyes met criteria for inclusion in the data analysis. Using the Holladay1 formula, the proportion of eyes with (n = 329) and without (n = 236) a score of 5 that achieved an outcome within 0.5 D of predicted was 78% and 69%, respectively(p<.001). Outcomes with the SRK/T formula were similar, with 75% (n=316) and 67% (n=230) of eyes, respectively(p<.001), achieving a refractive outcome within 0.5 D.

Conclusions : Applying validation criteria to biometric indices allows one to predict which eyes will have superior refractive outcomes after cataract surgery. The aforementioned scoring system may be useful as a pre-operative counseling tool to help inform patients of their expected post-operative refractive outcome. Further data analysis will allow us to predict outcomes with more granularity than in our own previous investigations.

This is a 2020 ARVO Annual Meeting abstract.

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