Investigative Ophthalmology & Visual Science Cover Image for Volume 61, Issue 7
June 2020
Volume 61, Issue 7
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ARVO Annual Meeting Abstract  |   June 2020
The Effects of Ocular Biometric Parameters on the Accuracy of IOL Power Calculation
Author Affiliations & Notes
  • Cynthia Chelsea Jiang
    Long School of Medicine, UT Health San Antonio, San Antonio, Texas, United States
  • Noah Michael Hodson
    Long School of Medicine, UT Health San Antonio, San Antonio, Texas, United States
  • Daniel A Johnson
    Ophthalmology, UT Health San Antonio, San Antonio, Texas, United States
  • Ahmad Kheirkhah
    Ophthalmology, UT Health San Antonio, San Antonio, Texas, United States
  • Footnotes
    Commercial Relationships   Cynthia Jiang, None; Noah Hodson, None; Daniel Johnson, None; Ahmad Kheirkhah, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 591. doi:
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      Cynthia Chelsea Jiang, Noah Michael Hodson, Daniel A Johnson, Ahmad Kheirkhah; The Effects of Ocular Biometric Parameters on the Accuracy of IOL Power Calculation. Invest. Ophthalmol. Vis. Sci. 2020;61(7):591.

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

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Abstract

Purpose : Many studies have investigated the role of axial length on accuracy of formulas for intraocular lens (IOL) power calculation. However, effects of other ocular biometric parameters have not been well studied. In this study, we evaluated the effects of these parameters on the accuracy of different formulas for IOL power calculation.

Methods : This retrospective study included 599 eyes which underwent cataract surgery with implantation of a foldable IOL (SN60WF in 373, ZCB00 in 184, SA60AT in 18, PCB00 in 12, SN60AT in 8, and SA60WF in 4). We excluded eyes with previous refractive surgery, associated corneal or anterior segment abnormalities, or intraoperative complications. The following parameters were extracted from measurements by IOL-Master: IOL power, keratometry (KR), anterior chamber depth (ACD), lens thickness (LT), and white-to-white measurement (WTW). Postoperative refraction at 1-3 months was then compared with the predicted power of the IOL as measured by Barrett Universal II, Holladay 2, SRK/T, Hoffer-Q, and Haigis formulas. Linear regression was used to determine the biometric parameters with significant association with the difference between postoperative refraction and predicted refraction (refractive prediction error or RPE).

Results : RPE had significant associations with different biometric parameters for different formulas (Table 1). The only biometric parameter that had significant positive association with RPE for all formulas was LT. The mean RPE for eyes with LT<5 mm and LT≥5 mm was 0.17 vs 0.36 D for Barrett Universal II (P=0.009), 0.14 vs 0.42 D for Holladay 2 (P<0.001), 0.20 vs 0.44 D for SRK/T (P<0.001), 0.23 vs 0.40 D for Hoffer-Q (P<0.001), and -0.03 vs 0.14 D for Haigis (P=0.02), respectively. Percentage of eyes within ±0.5 D of the target refraction for eyes with LT<5 mm and LT≥5 mm was 77.7 vs 68.9% for Barrett, 67.4 vs 59.5% for Holladay 2, 67.0 vs 60.7% for SRK-T, 63.0 vs 60.4% for Hoffer-Q, and 64.9 vs 54.0% for Haigis, respectively.

Conclusions : Accuracy of various IOL power formulas has significant association with different ocular biometric parameters. Eyes with higher LT are associated with higher RPE after cataract surgery.

This is a 2020 ARVO Annual Meeting abstract.

 

Table 1. Ocular biometric parameters with significant association with refractive prediction error for different formulas.

Table 1. Ocular biometric parameters with significant association with refractive prediction error for different formulas.

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