Rabiolo, Alessandro; Montesano, Giovanni; Crabb, David P; Garway-Heath, David F; United Kingdom Glaucoma Treatment Study Investigators, .; (2024) Relationship between intraocular pressure fluctuation and visual field progression rates in the United Kingdom Glaucoma Treatment Study. Ophthalmology 10.1016/j.ophtha.2024.02.008. (In press).

Text 1-s2.0-S0161642024001234-main.pdf - Accepted Version Access restricted to UCL open access staff until 14 February 2025. Download (1MB)

Abstract

Purpose: To investigate whether intraocular pressure (IOP) fluctuation is independently associated with the rate of visual field (VF) progression in the United Kingdom Glaucoma Treatment Study.// Design: Randomized, double-masked, placebo-controlled multicenter trial.// Participants: Participants with ≥5 VFs (213 placebo, 217 treatment).// Methods: Associations between IOP metrics and the VF progression rates (mean deviation (MD) and five fastest locations) were assessed with linear mixed models. Fluctuation variables were mean ocular pulse amplitude (OPA), standard deviation (SD) of diurnal IOP (diurnal fluctuation), and SD of IOP at all visits (long-term fluctuation). Fluctuation values were normalized for mean IOP to make them independent from mean IOP. Correlated non-fluctuation IOP metrics (baseline, peak, mean, supine and peak phasing IOP) were combined with principal component analysis (PCA), and principal component 1 (PC1) was included as a covariate. Interactions between covariates and time from baseline modelled the effect of the variables on VF rates. IOP was measured with Goldmann applanation tonometry and OPA with Pascal tonometry. Analyses were conducted separately in the two treatment arms.// Main Outcome Measures: Associations between IOP fluctuation metrics and rates of MD and five fastest test locations.// Results: In the placebo arm, only PC1 was significantly associated with the MD rate (estimate [standard error (SE)]: -0.19 [0.04] dB/year, p<0.001), while normalized IOP fluctuation metrics were not. No variable was significantly associated with MD rates in the treatment arm. For the fastest five locations in the placebo group, PC1 (estimate [SE]: -0.58 [0.16] dB/year, p<0.001), CCT (estimate [standard error (SE)]: 0.26 [0.10] dB/year for 10 μm thicker, p=0.01) and normalized OPA (estimate [SE]: -3.50 [1.04] dB/year, p=0.001) were associated with rates of progression; normalized diurnal and long-term IOP fluctuations were not. In the treatment group, only PC1 (estimate [SE]: -0.27 [0.12] dB/year, p=0.028) was associated with the rates of progression.// Conclusions: There is no evidence to support that either diurnal or long-term IOP fluctuation, as measured in clinical practice, are independent factors for glaucoma progression; other aspects of IOP, including mean IOP and peak IOP, may be more informative. OPA may be an independent factor for faster glaucoma progression.

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