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Background: Glaucoma is an optic neuropathy characterized by retinal ganglion cells (RGC) loss and retinal nerve fiber layer (RNFL) injury: this results in functional and morphological changes. The first can be observed by Standard Automated Perimetry (SAP), the second by Optic Coherence Tomography (OCT) that measures the RNFL and ganglion cell complex (GCC) thicknesses. Nevertheless, diagnosis of early glaucoma may be difficult. Recently, Medeiros et al. derived an empirical formula combining the measurement of structural and functional tests to provide an estimate of RGC. The aim of the current study is to analyse the correlation between RGC count, estimated by Medeiros' formula, and the structural and functional parameters in patients examined for glaucoma and to evaluate SAP, OCT and RGC counts capability to discriminate the weight of the disease itself., Methods: Ninety four eyes of 50 consecutive patients clinically referring to glaucoma service of the Universitary Eye Clinic were submitted to a complete ophthalmic evaluation including SAP and Spectral Domain OCT (SD-OCT) of RNFL and macular GCC. Average thickness of RNFL and macular GCC, parameters Global Loss Volume (GLV) and Focal Loss Volume (FLV) over the entire GCC map were taken into account. Estimates of RGC were obtained with the help of a model already published by Medeiros et al. combining light sensitivities from SAP and retinal thickness from OCT. The RGC count was estimated in the entire visual field (central 24°) and in the GCC macular area and then compared with functional and morphological parameters applying Pearson's correlation coefficient., Results: After the classification of the patients by the Glaucoma Staging System 2 of Brusini, we noticed a good correlation among the functional parameters considered, even if the Visual Field Index is unable to identify early glaucoma. An analogous result can be observed for structural data (RNFL and GCC). The correlation detected between functional and structural parameters was moderate. Great differences in RGC counts were found between groups at various stages of glaucoma. GLV showed highest level of correlation (r > -0.8) with RCG counts., Conclusions: Estimate circumpapillary and macular RGC counts can discriminate various stages of the disease and there is also a good/very good correlation with both functional and structural parameters. GLV could be used instead of RGC counts in clinical practice.