July 2019
Volume 60, Issue 9
Free
ARVO Annual Meeting Abstract  |   July 2019
Optimizing prediction of refractive outcomes after cataract surgery using a biometry-based scoring rubric
Author Affiliations & Notes
  • Diane Haeji Jang
    Penn State College of Medicine, Hershey, Pennsylvania, United States
  • Andrew Luo
    Penn State College of Medicine, Hershey, Pennsylvania, United States
  • Jack Quillen
    Ophthalmology, Penn State Milton S. Hershey Medical Center, Pennsylvania, United States
  • Tara O'Rourke
    Ophthalmology, Penn State Milton S. Hershey Medical Center, Pennsylvania, United States
  • Ingrid U Scott
    Ophthalmology, Penn State Milton S. Hershey Medical Center, Pennsylvania, United States
    Public Health Sciences, Penn State College of Medicine, Pennsylvania, United States
  • Seth Pantanelli
    Ophthalmology, Penn State Milton S. Hershey Medical Center, Pennsylvania, United States
  • Footnotes
    Commercial Relationships   Diane Haeji Jang, None; Andrew Luo, None; Jack Quillen, None; Tara O'Rourke, None; Ingrid Scott, None; Seth Pantanelli, Carl Zeiss Meditec (C)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 479. doi:
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    • Get Citation

      Diane Haeji Jang, Andrew Luo, Jack Quillen, Tara O'Rourke, Ingrid U Scott, Seth Pantanelli; Optimizing prediction of refractive outcomes after cataract surgery using a biometry-based scoring rubric. Invest. Ophthalmol. Vis. Sci. 2019;60(9):479.

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

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Abstract

Purpose : Intraocular lens (IOL) power prediction formulas are known to perform better for eyes with normal biometry compared to eyes 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 was to develop a scoring rubric that stratifies eyes with normal and eccentric biometric values and to investigate whether such a rubric may be used to differentiate eyes with versus without an exceptionally high likelihood of good refractive outcomes.

Methods : Retrospective consecutive case series of all eyes that underwent cataract surgery with implantation of a one-piece aspheric acrylic IOL (Bausch & Lomb MX60) between January 2016 and December 2017 by, or supervised by, a single surgeon at an academic medical center. Eyes were scored by five validation criteria establishing upper and lower boundaries for normal axial length, keratometry, anterior chamber depth, lens thickness, and white-to-white. One point was given for each criterion met. 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 : A total of 240 eyes met inclusion and exclusion criteria. Using the Holladay2 formula, the proportion of eyes with (n = 122) and without (n = 118) a score of 5 (n = 122) that achieved a refractive outcome within 0.25 D of predicted was 47.5% and 38.1%, respectively (p = 0.15); the proportion that achieved an outcome within 0.5 D of predicted was 78.7% and 68.6%, respectively (p = 0.08). Outcomes with the Barret Universal II formula were similar; the proportion with and without a score of 5 that achieved an outcome within 0.25 D of predicted was 55.7% and 44.1%, respectively, and the proportion that achieved an outcome within 0.5 D of predicted was 81.1% and 78.0%, respectively.

Conclusions : Biometric indices may be used to predict which eyes will have superior refractive outcomes after cataract surgery. The aforementioned scoring system may be useful preoperatively as a counseling tool to help inform patients of expected post-operative refractive outcomes.

This abstract was presented at the 2019 ARVO Annual Meeting, held in Vancouver, Canada, April 28 - May 2, 2019.

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