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David P. Piñero, Jorge L. Alio, Miguel A. Teus, Rafael I. Barraquer, Antonio Uceda-Montañés; Modeling the Intracorneal Ring Segment Effect in Keratoconus Using Refractive, Keratometric, and Corneal Aberrometric Data. Invest. Ophthalmol. Vis. Sci. 2010;51(11):5583-5591. doi: https://doi.org/10.1167/iovs.09-5017.
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© ARVO (1962-2015); The Authors (2016-present)
To characterize the refractive, keratometric, and corneal aberrometric effect of a specific type of intracorneal ring segment (ICRS) as a function of its thickness and the preoperative conditions of the cornea.
A total of 72 consecutive keratoconic eyes of 57 patients ranging in age from 15 to 68 years were retrospectively analyzed and included in the study. All cases had a diagnosis of keratoconus and had undergone implantation of a 160° arc-length KeraRing segment (Mediphacos, Belo Horizonte, Brazil), by femtosecond laser technology. Correlations between ring segment thickness and several clinical parameters were investigated. In addition, a multiple regression analysis was performed to characterize all factors that influence the ring segment effect.
Significant reductions in central curvature, corneal astigmatism, and comalike aberrations were found after surgery (P ≤ 0.03). Moderate and limited correlations were found between ring segment thicknesses and changes in mean keratometry and higher order aberrations (r ≤ 0.50, P < 0.01). A consistent linear relationship of the superior ring segment thickness to the induced corneal changes, the preoperative cylinder, and the difference in thickness between inferior and superior segments was found (P < 0.01, R 2 = 0.91). An almost identical model was obtained for the inferior ring segment thickness with the only distinction in the factor being the thickness difference between segments (P < 0.01, R 2 = 0.64).
The selection of the ring segment to implant in keratoconus should be based, not only on refraction and subjective appearance of the corneal topographic pattern but also on corneal aberrometry. This highly customized selection would allow a more predictable outcome.
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