The effect of ocular biometric factors on the accuracy of various IOL power calculation formulas

Jeong, Jinho; Song, Hyun-Ok; Lee, Jimmy K.; Chuck, Roy S.; Kwon, Ji Won

doi:10.1186/s12886-017-0454-y

Cited by 50 publications

(39 citation statements)

References 18 publications

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“…This supports previously published research on biometric determinants for cataract and refractive surgery (Engren & Behndig ; Jeong et al. ; Plat et al. ).…”

Section: Discussionsupporting

confidence: 92%

Correlations between ocular biometrics and refractive error: A systematic review and meta‐analysis

Gaurisankar

Rijn

Lima

et al. 2019

Acta Ophthalmologica

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The understanding of correlations between different biometric parameters is essential for personalized eye care in the field of cataract and refractive surgery. This systematic review offers a clear overview of the previous literature assessing these correlations including a meta-analysis. The review is focused on the following five correlations: (1) axial length and refractive error; (2) anterior chamber depth and refractive error; (3) axial length and anterior chamber depth; (4) corneal power and refractive error; (5) corneal power and axial length. An expected strong correlation between axial length and refractive error was found. Correlations including corneal power were weak and might be clinically insignificant.

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“…This supports previously published research on biometric determinants for cataract and refractive surgery (Engren & Behndig ; Jeong et al. ; Plat et al. ).…”

Section: Discussionsupporting

confidence: 92%

Correlations between ocular biometrics and refractive error: A systematic review and meta‐analysis

Gaurisankar

Rijn

Lima

et al. 2019

Acta Ophthalmologica

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“…Jeong et al reported that preoperative ACD has the greatest influence in IOL power calculation of the third-generation formulas and the Haigis formula. [ 20 ]…”

Section: Discussionmentioning

confidence: 99%

Effect of anterior chamber depth on the choice of intraocular lens calculation formula

2017

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PurposeTo investigate the effect of anterior chamber depth (ACD) on the refractive outcomes of the SRK/T, Holladay 1, Hoffer Q and Haigis formulae in short, normal, long and extremely long eyes.MethodsThis retrospective study involved patients who had uncomplicated cataract surgery. Preoperative axial length (AL) was divided into four subgroups: short (< 22.00 mm), normal (22.00–24.49 mm), long (24.50–25.99 mm), extremely long (≥ 26.00 mm). Preoperative ACD was divided into three subgroups: < 2.5, 2.50–3.49, and ≥ 3.5 mm. Median absolute errors (MedAEs) predicted by the SRK/T, Holladay 1, Hoffer Q and Haigis formulae were compared with the Friedman test. Post-hoc analysis involved the Wilcoxon signed rank test with a Bonferroni adjustment. Correlations between ACD and the predictive refractive errors of the four formulas were analyzed.ResultsIn short eyes with an ACD < 2.5 mm, the Haigis formula revealed the highest MedAE. The difference in MedAE with the Hoffer Q formula (which had the lowest MedAE) was statistically significant (P = 0.002). In normal eyes, the Haigis formula significantly differed from the Holladay 1 (P = 0.002) and Hoffer Q (P = 0.005) formulae in the ACD < 2.5 mm group. In long eyes and extremely long eyes with an ACD ≥ 3.5 mm, the differences in MedAEs were statistically significant (P = 0.018, P = 0.001, respectively) and the Haigis formula had the lowest MedAEs in both subgroups (0.29 D, 0.30 D, respectively). In the total of 1,123 eyes, refractive errors predicted by the Haigis formula showed a significant negative correlation with the ACD (R2 = 0.002, P = 0.047).ConclusionsThe Hoffer Q formula is preferred over other formulae in short eyes with an ACD shallower than 2.5 mm. In short and normal eyes with an ACD < 2.5 mm the Haigis formula might underestimate ELP. The Haigis formula is the preferred choice in eyes with an AL ≥ 24.5 mm and an ACD ≥ 3.5 mm.

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“…4,5) Some studies have analyzed the influence of preoperative anterior chamber depth (ACD) on PPR in different IOL calculation formulas. 6,7) They concluded that the influence of preoperative of ACD on PPR varies from formula to formula. Other studies have examined the influence of pupil dilation on biometric parameters such as ACD, lens thickness (LT), white-to-white (WTW), and recommended IOL power using different IOL calculation formulas.…”

Section: Introductionmentioning

confidence: 99%

Influence of pupil dilation on the Barrett Universal II (new generation), Haigis (4th generation), and SRK/T (3rd generation) intraocular lens calculation formulas: a retrospective study

Teshigawara

Meguro

Mizuki

2020

Preprint

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Background: We investigated the effect of pupil dilation on predicted postoperative refraction (PPR) and recommended intraocular lens (IOL) power calculated using three different generations of IOL power calculation formulas: Barrett Universal II (Barrett) (new generation), Haigis (4th generation), and SRK/T (3rd generation). Methods: This retrospective study included 150 eyes. All variables were measured and calculated using a ZEISS IOL Master 700. The following variables were measured before and after dilation: anterior chamber depth (ACD), lens thickness (LT), white-to-white (WTW). PPR and recommended IOL power were calculated by Barrett, Haigis, and SRK/T IOL calculation formulas. The change in each variable before and after dilation, and correlations between all changes were analyzed using the Wilcoxon signed-rank test and the Spearman’s rank-order correlation test, respectively. The influence of pupil dilation on recommended IOL power calculated by each formula was also analyzed. Results: The mean absolute change (MAC) in PPR before and after dilation was highest in Barrett, followed by Haigis and SRK/T. Significant differences were found among each MACs (P < 0.0001). Significant changes were observed before and after dilation in ACD and LT (P < 0.0001) but not in WTW. In Barrett and Haigis, there was a significant positive correlation between change in PPR and change in ACD (P < 0.0001) and a negative correlation between change in PPR and change in LT (P < 0.0001). Correlations were strongest in Barret followed by Haigis, especially in LT. Change in PPR in Barrett also demonstrated a significant positive correlation with change in WTW (P = 0.022). The recommended IOL power using Barrett and Haigis changed before and after dilation in 23.3% and 19.3% cases; SRK/T showed no change. Conclusions: In PPR and recommended IOL power, pupil dilation influenced Barrett most strongly, followed by Haigis and SRK/T. Given the stronger correlation between the change in PPR in Barrett and the change in ACD, LT, and WTW, the change of ACD, LT, and WTW is more important to the influence of dilation on Barrett. The influence of dilation on each formula and variable, including ACD, LT, and WTW, is key to improving IOL calculation.

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The effect of ocular biometric factors on the accuracy of various IOL power calculation formulas

Cited by 50 publications

References 18 publications

Correlations between ocular biometrics and refractive error: A systematic review and meta‐analysis

Correlations between ocular biometrics and refractive error: A systematic review and meta‐analysis

Effect of anterior chamber depth on the choice of intraocular lens calculation formula

Influence of pupil dilation on the Barrett Universal II (new generation), Haigis (4th generation), and SRK/T (3rd generation) intraocular lens calculation formulas: a retrospective study

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