Best model in multiple regression analysis to predict GAL-9 scores.

<p>Adding any sector of the RNFL or age did not enhance the predictive power.</p

Demographic, biometric and clinical characteristics including the spectral-domain optical coherence tomography (SD-OCT) assessed retinal nerve fibre layer (RNFL) thickness (mean values +/- 1 SD).

<p>Demographic, biometric and clinical characteristics including the spectral-domain optical coherence tomography (SD-OCT) assessed retinal nerve fibre layer (RNFL) thickness (mean values +/- 1 SD).</p

Univariate linear regression.

<p>Dependent variable GAL-9. Visual acuity (VA) and mean defect (MD) were significant predictors for GAL-9 scores with the MD of the better eye revealing best modelling (R²=0.279). The only significant predictor of structural parameters was the retinal nerve fibre layer (RNFL) of the temporal superior (TS) sector of the worse eye. IOP: intraocular pressure, CCT: central corneal thickness, PSD: pattern standard deviation, CDR: cup-to-disc ratio.</p

Correlation analysis between important functional parameters and IOP, CCT and RNFL sectors (T: temporal, TS: temporal superior, NS: nasal superior, N: nasal, NI: nasal inferior, TI: temporal inferior, G: global) for better eye (b/e) and worse eye (w/e), respectively.

<p>Cursive numbers are Pearson´s correlation coefficients, otherwise Spearman rank coefficients are displayed. Significant coefficients (p<0.05) are bold.</p