Factors associated with refractive prediction error after phacotrabeculectomy

INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE(2023)

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摘要
Abstract Background: To compare refractive prediction errors between phacotrabeculectomy and phacoemulsification. Methods: Refractive prediction error was defined as the difference of spherical equivalent between the predicted value using the Barrett Universal II formula and the actual value obtained at postoperative one month. Forty-eight (48) eyes that had undergone uncomplicated phacotrabeculectomy (19 eyes, open-angle glaucoma; 29 eyes, angle-closure glaucoma) were matched with 48 eyes that had undergone uncomplicated phacoemulsification by age, average keratometry value and axial length, and their prediction errors were compared. The factors associated with prediction error were analyzed by multivariable regression analyses. Results: The absolute prediction error was larger in the phacotrabeculectomy group than in the phacoemulsification group (0.51 ± 0.37 Diopters vs. 0.38 ± 0.22, P =0.033). Larger absolute prediction error was associated with both longer axial length ( P =0.010) and higher intraocular pressure difference ( P =0.012). A logistic regression analysis showed that hyperopic shift (prediction error>0) was associated with shallower preoperative anterior chamber depth ( P =0.024)and larger intraocular pressure difference ( P =0.031). In the phacotrabeculectomy group, the prediction error was inversely correlated with axial length: long eyes showed myopic shift and short eyes hyperopic shift ( P =0.002). Conclusions: Intraocular lens (IOL) power calculation might be less accurate in phacotrabeculectomy than in phacoemulsification due to large axial length and anterior chamber depth changes with intraocular pressure lowering. Surgeons therefore should be aware of the possibility of worse refractive outcomes when planning phacotrabeculectomy especially in eyes with high preoperative intraocular pressure, shallow anterior chamber depth, and/or extreme axial length.
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refractive prediction error
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