Intraocular Lens Power Formulas, Biometry, and Intraoperative Aberrometry

Kane, Jack X; Chang, David F.

doi:10.1016/j.ophtha.2020.08.010

Cited by 75 publications

(53 citation statements)

References 154 publications

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“…Previous studies have reported that the Kane formula and traditional formulas with WK AL adjustment exhibited higher prediction accuracy in highly myopic eyes. [23][24][25][26][27][28][29] In this study, we also observed that Kane and traditional formulas with WK AL adjustment displayed better prediction accuracy in PIOL implanted eyes. This could be partly due to that the study participants were all highly myopic with an average AL of 31.43 ± 2.15 mm.…”

Section: Discussionmentioning

confidence: 56%

Accuracy of Intraocular Lens Calculation Formulas in Patients Undergoing Combined Phakic Intraocular Lens Removal and Cataract Surgery

Zhang

Han

Liu

et al. 2022

American Journal of Ophthalmology

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Section: Discussionmentioning

confidence: 56%

Accuracy of Intraocular Lens Calculation Formulas in Patients Undergoing Combined Phakic Intraocular Lens Removal and Cataract Surgery

Zhang

Han

Liu

et al. 2022

American Journal of Ophthalmology

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“…The second problem is that we did not compare our formula with Kane’s one, because we emphasized the fact that many papers have shown that the Barrett Universal II formula is the best [ 5 , 6 , 7 ]. However, in terms of the number of cases studied, it is reasonable to point out that Kane’s formula is the most accurate, [ 8 ] and further studies to compare our formula with Kane’s one are needed.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, several papers that used numerous intraocular lens (IOL) power calculation formulas in predicting postoperative refraction have been published, and recent reports have indicated that the Barrett Universal II formula has high accuracy [ 5 , 6 , 7 ]. On the other hand, Kane et al recently reported that Kane’s formula has higher accuracy in studies with many cases [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Use of a Machine Learning Method in Predicting Refraction after Cataract Surgery

Yamauchi¹,

Tabuchi

Takase³

et al. 2021

JCM

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The present study aims to describe the use of machine learning (ML) in predicting the occurrence of postoperative refraction after cataract surgery and compares the accuracy of this method to conventional intraocular lens (IOL) power calculation formulas. In total, 3331 eyes from 2010 patients were assessed. The objects were divided into training data and test data. The constants for the IOL power calculation formulas and model training for ML were optimized using training data. Then, the occurrence of postoperative refraction was predicted using conventional formulas, or ML models were calculated using the test data. We evaluated the SRK/T formula, Haigis formula, Holladay 1 formula, Hoffer Q formula, and Barrett Universal II formula (BU-II); similar to ML methods, we assessed support vector regression (SVR), random forest regression (RFR), gradient boosting regression (GBR), and neural network (NN). Among the conventional formulas, BU-II had the lowest mean and median absolute error of prediction. Therefore, we compared the accuracy of our method with that of BU-II. The absolute errors of some ML methods were lower than those of BU-II. However, no statistically significant difference was observed. Thus, the accuracy of our method was not inferior to that of BU-II.

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“…10 It has been demonstrated that eyes with longer axial length and flatter keratometry showed more hyperopic outcomes, when the SRK/T formula was applied without adjustments, [11][12][13] and that the latest generation formulas, such as the Barrett Universal II formula, the Hill RBF V.2 method and the Kane formula, were less subjected to biometrical variations in the axial length and the keratometric readings. [14][15][16][17] A further study using these new generation formulas is required to clarify this point. Fourth, we used two different optical biometers (IOLMaster 700 at nine institutions and OA-2000 at three institutions) for this evaluation, since there are some variations in optical biometers for clinical use in Japan.…”

Section: Clinical Sciencementioning

confidence: 99%

Nationwide multicentre comparison of preoperative biometry and predictability of cataract surgery in Japan

Kamiya

Hayashi

Tanabe³

et al. 2021

Br J Ophthalmol

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AimTo compare the preoperative biometric data and the refractive accuracy of cataract surgery among major surgical sites in a nationwide multicentre study.MethodsWe prospectively obtained the preoperative biometric data of 2143 eyes of 2143 consecutive patients undergoing standard cataract surgery at major 12 facilities and compared the preoperative biometry as well as the postoperative refractive accuracy among them.ResultsWe found significant differences in most preoperative variables, such as axial length (one-way analysis of variance, p=0.003), anterior chamber depth (p<0.001), lens thickness (p<0.001) and central corneal thickness (p<0.001), except for mean keratometry (p=0.587) and corneal astigmatism (p=0.304), among the 12 surgical sites. The prediction error using the Sanders-Retzlaff-Kraff/Theoretical (SRK/T formula was significantly more hyperopic than that using the Barrett Universal II formula (paired t-test, p<0.001). The absolute error using the SRK/T formula was significantly larger than that using the Barrett Universal II formula (p=0.016). The prediction error using the SRK/T formula was significantly more hyperopic than that using the Barrett Universal II formula at 10 of 12 institutions, but significantly more myopic at one institution. The absolute error using the SRK/T formula was significantly larger than that using the Barrett Universal II formula at 4 of 12 institutions but significantly smaller at two institutions.ConclusionsRegional divergences of the preoperative biometry were not necessarily negligible, and the optimised intraocular lens power calculation formula was individually different among the 12 facilities. Our findings highlight the importance of individual optimisation of these formulas at each facility, especially in consideration of these biometric variations.Trial registration numberClinical Trial Registry; 000039976.

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Intraocular Lens Power Formulas, Biometry, and Intraoperative Aberrometry

Cited by 75 publications

References 154 publications

Accuracy of Intraocular Lens Calculation Formulas in Patients Undergoing Combined Phakic Intraocular Lens Removal and Cataract Surgery

Accuracy of Intraocular Lens Calculation Formulas in Patients Undergoing Combined Phakic Intraocular Lens Removal and Cataract Surgery

Use of a Machine Learning Method in Predicting Refraction after Cataract Surgery

Nationwide multicentre comparison of preoperative biometry and predictability of cataract surgery in Japan

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