Prediction of the effective postoperative (intraocular lens) anterior chamber depth

Publisher Website
Google Scholar
Abstract
Tive refractive results, the postoperative effective ACD was calculated in each case and studied by multiple linear regression for covariance with a number of preoperatively defined variables including the axial length by ultrasonography, preoperative ACD, lens thickness, corneal radius by keratometry, subjective refraction, patient age, and corneal white-to-white diameter, the latter of which was available in a subgroup of 900 cases. RESULTS: The postoperative effective ACD was significantly correlated with 6 preoperative variables (in decreasing order): axial length, preoperative ACD, keratometry reading, lens thickness, refraction, and patient age (R = 0.49, P<.000001). Age showed the weakest correlation (P = .02) and could be omitted with no significant decrease in the total correlation coefficient. Using the 5 most significant variables, the ACD could be predicted according to a regression formula with an accuracy of 82.1% of the predictions within 0.5 mm. When this ACD algorithm was used in retrospect in the intraocular lens (IOL) power calculation, the refractive prediction error decreased by 10% from the error associated with a previously published 4-variable algorithm and decreased 28% from the error using no individual ACD method other than the average ACD (P<.00001). CONCLUSIONS: The postoperative ACD was significantly correlated with and hence predictable by a 5-variable regression method incorporating the preoperative axial length, ACD, keratometry reading, lens thickness, and refraction as the most significant variables. The statistical relationship can be used to create a new ACD prediction algorithm to incorporate in a modern “thick lens” IOL power calculation formula with significant improvement in the accuracy of the refractive predictions as a result....

This publication has 25 references indexed in Scilit: