Accuracy of Artificial Intelligence Formulas and Axial Length Adjustments for Highly Myopic Eyes

PURPOSE: To compare the accuracy of artificial intelligence formulas (Kane formula and Radial Basis Function [RBF] 2.0) and other formulas, including the original and modified Wang-Koch (MWK) adjustment formulas for Holladay 1 (H1-MWK) and SRK/T (SRK/T-WK and SRK/T-MWK), the Barrett Universal II (BUII), the emmetropia-verifying optical (EVO), and the Haigis equation in highly myopic eyes. DESIGN: Retrospective consecutive case-series study. METHODS: A total of 370 eyes with an axial length (AL) 226.0 mm of 370 patients were enrolled, and subgroup analyses was performed based on ALs. The median absolute error (MedAE), the percentages of eyes with hyperopic outcome and within +/- 0.25 diopters (D), +/- 0.50 D, and +/- 1.00 D of prediction error were determined. RESULTS: Overall, the Kane equation had the lowest MedAE (0.26 D), followed by H1-WK (0.27 D) and H1-MWK (0.28 D). There were no significant differences in MedAE among the Kane equation, the RBF 2.0, the BUII, the H1-MWK, and the H1-WK, whereas the Kane equation had a significantly lower MedAE than EVO (P < .001), SRK/T-MWK (P = .001), SRK/TWK (P = .006), and Haigis (P < .001). In extremely myopic eyes with an AL 230.0 mm (n = 115), the Kane equation had a significantly lower MedAE than the RBF 2.0 (P = .001), the EVO (P = .019), the BUII (P = .013), and the Haigis method (P = .005), whereas no significant differences were found among the Kane, H1-MWK, and H1-WK equations. CONCLUSIONS: The Kane equation was comparable to RBF 2.0, BUII, H1-MWK, and H1-WK in highly myopic eyes and was better than RBF 2.0 and BUII in extremely myopic eyes. The Kane, H1-MWK, and H1-WK methods were equally accurate in eyes with high to extreme myopia.