Comprehensive Summary
This paper, presented by Sapok et al., evaluates the accuracy of intraocular lens calculation formulas among patients who undergo triple DMEK and cataract surgery. With the known struggles of IOL calculation due to failure to account for postoperative hyperopic shift, the paper aims to compare modern IOL calculations to see which calculation can lead to the most accurate outcome among patients. Specifically, they covered eleven different calculation techniques. Medical records of patients going through both cataract and DMEK surgery at Goethe University, Frankfurt, Germany from 2016-2023 were reviewed and used as data for the study. The study included only eyes that used a single monofocal IOL model. The evaluation process consisted of comparing the predicted postoperative refraction with the post clinical postoperative refraction. Error analysis was performed in Excel and SPSS utilizing Shapiro-Wilk, Friedman, and Cochran Q tests. The results demonstrated that IOL calculation with BUII method appeared to have accurate results compared to the other nine calculations. Future studies should include IOL calculation that utilizes AI models as this study did not include AI models as part of the subjects included.
Outcomes and Implications
Sapok et al., in this study examines the effectiveness of different IOL calculation methods. The results of the study indicated that the BUII method presented the fewest errors compared to other models. In this specific model, the calculations account for hyperopic shift, the leading cause in miscalculations in previous IOL calculation methods. Other models that were relatively accurate were Pearl DGS and EVO, which accounted for the thickness of the patient's cornea. Despite the ranking, the overall difference between the different methods were statistically insignificant, indicating there are not many differences among accuracies between the different models. However, with the emergence of AI formulas, these formulas might provide more accurate results than traditional calculation methods due to their ability to analyze large datasets and use pattern recognition more effectively than traditional methods can.