This article is more than 5 years old. Information may no longer be current.
Publication Exclusive: Dynamic Ladas Super Surface helps optimize and refine IOL calculations
Click Here to Manage Email Alerts
Historically, we have been advised to optimize specific IOL formulae for our patients in order to better predict the postoperative refraction and to deliver better visual outcomes. This means that we need to analyze our patient data and then make adjustments so that future IOL calculations are more accurate.
The idea is that there are differences in calibration of the devices used in biometry and even differences in surgical techniques that can influence the IOL power calculation and thus the postoperative refractive result. This makes sense because if one keratometer reads 0.5 D different than another, there may be about a 0.5 D difference in IOL power if all other factors are equal. Surgical technique typically refers to steps that affect the effective lens position such as the overlap of the capsulorrhexis over the optic edge in order to secure it. A large, non-overlapping capsulorrhexis may allow the IOL optic to come forward, thereby resulting in a more myopic outcome.
Optimizing the A-constant for the SRK/T formula, the “Surgeon Factor” for the Holladay formula, the anterior chamber depth for the Hoffer Q, or the a0/a1/a2 for the Haigis will affect the IOL power evenly across the board, from the most hyperopic eye to the most myopic one. This optimization will help to some degree, but each IOL formula tends to have a “sweet spot” at which it is most accurate and also areas at which it is less precise. What we actually need to do, in order to improve accuracy, is optimize the formula across the spectrum and with all known variables.
It has been said that at least 20 eyes need to be considered to optimize IOL calculations with a particular formula. But what about comparing one formula with another? Do we need to go back and calculate scores of eyes in order to improve accuracy? Probably not because we would be better served to compare the two formulae and determine at which parameters there is a discrepancy between them. The Ladas-Siddiqui graph is a way of comparing two formulae across a range of biometric parameters. The area of clinical agreement can be identified as well as the area of discrepancy. For the best results, we should focus our efforts on the area of clinical disagreement because this is likely to yield the most benefit.
Click here to read the full publication exclusive, Back to Basics, published in Ocular Surgery News U.S. Edition, December 25, 2015.