scholarly journals Prediction error and accuracy of intraocular lens power calculation in pediatric patient comparing SRK II and Pediatric IOL Calculator

2010 ◽  
Vol 10 (1) ◽  
Author(s):  
Azlyn-Azwa Jasman ◽  
Bakiah Shaharuddin ◽  
Raja-Azmi M Noor ◽  
Shatriah Ismail ◽  
Zulkifli A Ghani ◽  
...  
2019 ◽  
Vol 30 (6) ◽  
pp. 1308-1313
Author(s):  
Gilles Lesieur

Purpose: To evaluate the potential benefit of a new version of an online toric intraocular lens calculator in eyes implanted with a bitoric intraocular lens. Patients and methods: Retrospective observational comparative study in patients that underwent cataract surgery with implantation of the bitoric intraocular lens AT TORBI 709M (Carl Zeiss Meditec AG, Jena, Germany). Visual and refractive outcomes were evaluated at 1 month after surgery. The selection of the toric intraocular lens power was performed with the software Z CALC 2.0 (Carl Zeiss Meditec AG). The absolute refractive prediction errors for the spherical equivalent and cylinder were calculated and compared with the values that would have been obtained using version 1.5 of the same software. Results: A total of 393 eyes of 276 patients were evaluated. Mean postoperative sphere and cylinder were +0.03 ± 0.54 and −0.19 ± 0.30 D, respectively. A total of 95.67%, 98.22%, and 95.17% of eyes had a postoperative sphere, cylinder, and spherical equivalent within ±1.00 D, respectively. Mean absolute refractive prediction error for spherical equivalent was 0.34 ± 0.27 D with the two versions of the Z CALC software. In contrast, a significantly higher absolute refractive prediction error value for the cylinder was found with Z CALC 1.5 compared to version 2.0 (0.35 ± 0.32 vs 0.28 ± 0.30 D, p < 0.001). The absolute refractive prediction error for cylinder was ⩽0.25 D in 62.3% and 47.5% when using the versions 2.0 and 1.5, respectively. Conclusion: The use of an optimized software for toric intraocular lens power calculation, considering the contribution of posterior corneal astigmatism, improved the astigmatic outcome with a bitoric intraocular lens.


2019 ◽  
Author(s):  
Hongyu Li ◽  
Jun Li ◽  
Hui Song

Abstract Background: To compare the accuracy of intraocular lens power calculation formulas after refractive surgery in myopic eyes. Methods: We searched the databases on the PubMed, EMBASE, Web of science and Cochrane library to select relevant studies published between Jan 1, 2009 and Aug 11, 2019. Primary outcomes were the percentages of refractive prediction error within ±0.5D and ±1.0D. Results: The results of this meta-analysis were investigated from 16 studies, including 7 common methods (Haigis-L, Shammas-PL, Double-K SRK/T, Barrett true K no history, Wang-Koch-Maloney, ASCRS average and OCT formula). ASCRS average yielded significantly higher percentage of refractive prediction error within ±0.5D than Haigis-L, Shammas-PL and W-K-M (P=0.009, 0.01, 0.008, respectively). Barrett true K no history also yielded significantly higher percentage of refractive prediction error within ±0.5D than Shammas-PL and W-K-M (P=0.01, <0.0001, respectively), and the same result was found by comparing OCT formula with Hiaigi-L and Shammas-PL (P=0.03, 0.01, respectively). Only the Haigis-L had significantly higher percentages than W-K-M method in the ±1.0D group (P = 0.04). Conclusion: We suggest that the ASCRS average and Barrett true K no history formula should be used to calculate the IOL power in eyes after myopic refractive surgery.


2021 ◽  
pp. 112067212110655
Author(s):  
Joaquim Fernández-Rosés ◽  
José Lamarca ◽  
David P. Piñero ◽  
Rafael I. Barraquer

Purpose To compare the accuracy of Sirius ray tracing software with the Barrett Universal II formula for intraocular lens power prediction in virgin eyes. Methods Retrospective case series including 86 eyes that have undergone uneventful cataract surgery with SN60WF implantation. The median absolute error, mean prediction error, variance, and the percentage of eyes within ± 0.25 D, ± 0.50 D, ± 0.75 D, and ± 1.00 D of the prediction error in refraction were calculated. The correlation of prediction error with different baseline parameters was investigated. Results No differences were found between the median absolute error of the Barrett Universal II formula (0.226 D) and the ray tracing software with different intraocular lens centerings; apex (0.331 D), limbus (0.345 D), and pupil (0.342 D) ( p = 0.084). The variance, from lowest to highest, was the Barrett Universal II (0.144 D2), ray tracing-limbus (0.285 D2), ray tracing-pupil (0.285 D2), and ray tracing-apex (0.287 D2) ( p = 0.027). The Barrett Universal II formula showed a higher percentage of eyes within ± 0.25 D (56.98%), ± 0.50 D (82.56%), and ± 0.75 D (93.02%) compared to ray tracing software ( p < 0.01). A significant correlation between the prediction error of the Barrett Universal II formula and corneal diameter (r = 0.322, p = 0.002) and pupil diameter (r = 0.230, p = 0.033) was found. Also, a positive correlation between the prediction error of Sirius ray tracing and axial length ( p < 0.001) and pupil diameter ( p = 0.01) was found. Conclusion There is a trend of the Barrett Universal II formula to be more accurate than Sirius ray tracing software for intraocular lens power calculation in virgin eyes. This should be confirmed in future prospective comparative studies.


2019 ◽  
pp. 112067211988901 ◽  
Author(s):  
Jiali Ji ◽  
Yan Liu ◽  
Jing Zhang ◽  
Xinhua Wu ◽  
Wanyu Shao ◽  
...  

Purpose: The aim of this study was to compare the accuracy of Barrett Universal II and Hill-Radial Basis Function with other four popular formulas for the calculation of intraocular lens power in high myopic eyes. Methods: A total of 56 eyes with an axial length of more than 26.0 mm were retrospectively reviewed. Six intraocular lens power calculation methods, including Barrett Universal II, Hill-Radial Basis Function, SRK/T, Haigis, Holladay 2 and Holladay 1, were evaluated. The difference between the postoperative actual refraction and the refraction predicted by the six methods was evaluated as the prediction error. The absolute prediction error was also calculated. Results: The mean numerical prediction error ± standard deviation of the six intraocular lens power calculation methods, in order of lowest to highest, was Barrett Universal II (0.37 ± 0.54 D), Hill-Radial Basis Function (0.40 ± 0.56 D), SRK/T (0.44 ± 0.56 D), Haigis (0.53 ± 0.54 D), Holladay 2 (0.88 ± 0.62 D) and Holladay 1 (1.00 ± 0.60 D). The median absolute errors predicted by the Barrett (0.46 D), Hill-Radial Basis Function (0.47 D), SRK/T (0.53 D) and Haigis (0.58 D) were significantly lower than those of the Holladay 1 (0.90 D) and Holladay 2(1.10 D; all p < 0.001). There was no significant difference among the median absolute errors of Barrett, Hill-Radial Basis Function, SRK/T and Haigis (all p > 0.05). Conclusion: The prediction errors differed for each method in the selection of intraocular lens power for the long eyes. In terms of overall accuracy, the Barrett Universal II formula provided the lowest prediction error. The Hill-Radial Basis Function method was comparable to the theoretical formulas, such as SRK/T and Haigis.


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