Acurácia das fórmulas biométricas na facectomia com implante de lente intraocular em uma população latino-americana

Abstract

Purpose: To observe performance of the main traditional IOL power calculation formulas (Barrett, Haigis, Hoffer Q, Holladay 1 e SRK/T) and the recent Kane and Pearl- DGS in different types of eyes in order to assist ophthalmologic surgeons in Latin America to provide better care to their patients with cataracts, thus obtaining results closer to those reported by international literature. Methods: Analytical, descriptive, observational, crosssectional, retrospective study, through the analysis of medical records of patients who underwent cataract surgery with intraocular lens implantation between February 2011 and March 2018, performed in a reference hospital in Brasília. In total, 1242 eyes were included and then separated according to axial length (AL) in the following subgroups: short (< 22.5mm), medium (22.5mm to 25.5mm) and long (> 25.5mm). The expected refractive result using four formulas was calculated and compared with the actual result to obtain the predicted error. Results: The mean absolute error (MAE) and the standard deviation (SD) found were equal to 0,410 +0,334 at Haigis, 0,417 +0,335 at Hoffer Q, 0,374 +0,311 at Holladay 1 and 0,610 +0,415 at SRK/T, in Barrett 0,370 +0,314, Kane 0,384 +0,322 and Pearl-DGS 0,360 +0,307. The Barrett and Pearl-DGS formula had the best performance in short and medium eyes, Barrett, Holladay 1, Kane and Pearl was the best results, while Barret was the best in long eyes. Six formulas showed convergence of predicted error in the value of AL equal to 20 a 25mm. The 42D < K mean < 46D interval showed the smallest predicted refractive errors. All formulas, with exception the SRK/T had a similar performance with ACD around 3 at 3.5mm. Conclusions: The population in question presented a behavior like the literature and, due to the sample size, there is the possibility of creating a support system for medical decision that helps the surgeon to select the best formula considering ocular biometrics.