Purpose To evaluate the refractive accuracy of current intraocular lens (IOL) formulas and propose a modification in calculation of corneal power in eyes undergoing combined cataract extraction and Descemet membrane endothelial keratoplasty (DMEK).
Design Retrospective cohort study.
Methods Patients with Fuchs endothelial corneal dystrophy undergoing uncomplicated combined cataract surgery and DMEK at a single institution were included. The Hoffer Q, SRK/T, Holladay I, Barrett Universal II and Haigis formulas were compared. A modified corneal power was calculated using a thick lens equation based on anterior and posterior corneal radii and corneal thickness from Pentacam imaging. Error calculations were adjusted based on the difference in optical biometry and the modified corneal power. Mean absolute error (MAE) for each formula was compared between the corneal power modification and optical biometry corneal power.
Results In 86 eyes, the mean error ranged from 0.90 D for the Barrett Universal II formula to −0.10 D for the Haigis formula, with 4 of 5 formulas resulting in a mean hyperopic error. The corneal power modification resulted in a significantly lower MAE for the Hoffer Q (0.82 D), Holladay I (0.85 D), SRK/T (0.85 D) and Barrett Universal II (0.90 D) formulas compared with optical biometry corneal power for the Hoffer Q (1.02 D; p<0.005), Holladay I (0.97 D; p<0.005), SRK/T (0.93 D; p<0.01) and Barrett Universal II (1.16 D; p<0.005) formulas.
Conclusions All formulas except the Haigis formula resulted in a hyperopic error. The corneal power modification significantly reduced error in four out of five IOL formulas.
- optics and refraction
Data availability statement
Data are available upon reasonable request. Data supporting our research are available upon a reasonable request.
Statistics from Altmetric.com
Contributors JAC, JGL, KW, FW and DS contributed to the design of the research, to the analysis of the results and to the writing of the manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests DS is a consultant for Alcon Laboratories. JGL is a principal for Advanced Euclidean Solutions. All other authors have no financial disclosures.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.