Purpose: To compare the performance of the Zeiss AI IOL Calculator (ZAIC) to that of Barrett Universal II (BUII) and Kane, using standard (K) and total keratometry (TK) as inputs. Patients and Methods: This was a multicenter retrospective case series which included surgery-naïve eyes undergoing cataract surgery with preoperative optical biometry on the IOLMaster 700, monofocal IOL (Bausch 0.38 vs 0.41 (p = 0.008) and 0.42 (p = 0.008)]. ZAIC also had a larger proportion of eyes within 0.5 D of predicted compared to BU2 K 82% vs 76% (p = 0.02), as well as a larger proportion of eyes within 0.75 D of predicted compared to BU2 TK 95% vs 91% (p = 0.02). There were no significant differences in MedAE or the proportion of eyes within 0.25 or 1 D of predicted. Conclusion: Compared to BU2, ZAIC produces a lower MAE, SD, and RMSAE, and a higher proportion of eyes within 0.5 and 0.75 D of predicted but performs similarly to Kane across all outcome measures. This remains true regardless of whether K or TK is used as an input. This study is limited by its retrospective design and use of a single MX60E IOL model. Plain Language Summary: This multi-institutional retrospective case series compares the prediction accuracy and precision of the Zeiss AI IOL Calculator (ZAIC) to the Barrett Universal II (BU2) and Kane intraocular lens power prediction formulas for cataract surgery. Results suggest ZAIC outperforms BU2 and performs at least as well as Kane. This holds true regardless of whether standard or total keratometry is used as formula inputs. This corroborates ZAIC as an accurate and precise tool for the preoperative selection of intraocular lens power, performing at least as well as other modern intraocular lens power calculation formulas. Keywords: cataract extraction, intraocular lens, artificial intelligence
Cannon et al. (Sun,) studied this question.