Long-term variability of retinal nerve fibre layer thickness measurement in patients with glaucoma of African and European descents

非洲裔和欧洲裔青光眼患者视网膜神经纤维层厚度测量的长期变异性

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Abstract

BACKGROUND: To examine long-term retinal nerve fibre layer thickness (RNFLT) variability and associated clinical factors in African (AD) and European descent (ED) individuals with glaucoma. METHODS: This retrospective cohort study included glaucoma eyes of AD and ED from Diagnostic Innovations in Glaucoma Study/The African Descent and Glaucoma Evaluation Study with ≥4 visits/2 years of follow-up. We calculated optic nerve head RNFLT variability per-examination/visit as the absolute error of its residuals across follow-up. Full, baseline and parsimonious linear-mixed models were fit to evaluate the effects of clinical factors (demographics and ocular characteristics, prior/intervening glaucoma surgeries and cataract extraction (CE), RNFLT thinning rate, scan quality, visit/testing frequency, etc) on RNFLT variability in both races. RESULTS: There were 376 and 625 eyes (226 and 349 participants) of AD and ED, and the mean (95% CI) RNFLT variability was 1.62 (1.52, 1.71) µm and 1.42 (1.34, 1.50) µm, respectively (p=0.002). AD and ED had some shared predictors of RNFLT variability, including intraocular pressure fluctuation and scan quality, although the effects varied (p<0.05). In both races, intervening CE was most strongly correlated with higher RNFLT variability (β: 0.24-0.92, p<0.05). After excluding eyes with intervening CE, RNFLT variability was reduced and the small racial difference was no longer significant (AD: 1.40 (1.31, 1.48) µm vs ED: 1.34 (1.27, 1.40) µm; p=0.280). CONCLUSIONS: Although some predictors were identified, long-term RNFLT variability appeared small for both AD and ED eyes. Moreover, the racial difference did not remain once intervening CE, the strongest predictor of variability, was eliminated. Our findings inform on strategies to optimise structural assessment and suggest that, when accounting for relevant factors, RNFLT is reliable across races.

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