Most cataract surgery outcomes datasets do not differentiate between biometrically normal eyes and those with extreme biometric values—often making it challenging to accurately predict post-op refractive outcomes.
Given that intraocular lens (IOL) power prediction formulas are known to perform better for normal eyes compared with eyes with highly variable values, researchers developed a scoring method that separates eyes with normal and eccentric biometric values. They found the new system, based on biometric indices, can help to predict which eyes will have superior refractive outcomes after cataract surgery. They shared their results at the 2019 ARVO conference in Vancouver. The team also believes the scoring system may be a useful preoperative counseling tool to help inform patients of their expected postoperative refractive outcomes.
This retrospective, consecutive case series evaluated 240 eyes that underwent cataract surgery and aspheric IOL implantation. The eyes were scored based on five validation criteria that established upper and lower boundaries for normal axial length, keratometry, anterior chamber depth, lens thickness and white-to-white. One point was given for each criterion met. Refractive outcomes for eyes that scored the maximum five points were compared with those that did not meet all criteria.
Using the new formula, the study authors discovered 47.5% of eyes with a score of five achieved a refractive outcome within 0.25D of what was predicted, compared with 38.1% of those that did not score five points. When accuracy was assessed within 0.5D of the predicted outcome, those numbers jumped to 78.7% for those that scored five points and 68.6% of those that did not.
Jang DH, Luo A, Quillen J, et al. Optimizing prediction of refractive outcomes after cataract surgery using a biometry-based scoring rubric. ARVO 2019. Abstract 479. |