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VOLUME 16 , ISSUE 2 ( May-August, 2022 ) > List of Articles

ORIGINAL RESEARCH

Pattern Electroretinogram Parameters and their Associations with Optical Coherence Tomography in Glaucoma Suspects

Andrew Tirsi, Amanda Wong, Daniel Zhu, Guillaume Stoffels, Peter Derr, MD Celso Tello

Keywords : Ganglion cell layer, Glaucoma, Glaucoma suspect, Inner plexiform layer, Macula, Optic nerve, Optical coherence tomography, Retinal ganglion cell, Retinal nerve fiber layer, Steady state pattern electroretinogram

Citation Information : Tirsi A, Wong A, Zhu D, Stoffels G, Derr P, Tello MC. Pattern Electroretinogram Parameters and their Associations with Optical Coherence Tomography in Glaucoma Suspects. J Curr Glaucoma Pract 2022; 16 (2):96-104.

DOI: 10.5005/jp-journals-10078-1365

License: CC BY-NC 4.0

Published Online: 30-08-2022

Copyright Statement:  Copyright © 2022; The Author(s).


Abstract

Aim: To investigate whether steady state pattern electroretinogram (ssPERG) could identify retinal ganglion cell (RGC) dysfunction, and to assess the relationship between ssPERG with optical coherence tomography (OCT) measurements in glaucoma suspects (GS). Materials and methods: This was a prospective cohort study of GS, identified based on suspicious optic disk appearance and glaucoma risk factors. Complete eye exam, Standard automated perimetry, OCT, and ssPERG were performed. Magnitude (Mag), Magnitude D (MagD), and MagD/Mag ratio were subsequently used in the correlation and linear regression analyses between ssPERG parameters and the RNFL, GCL/IPL, and macular thicknesses measurements. Results: Forty-nine eyes of 26 patients were included. Mag and MagD were significantly correlated with the superior, inferior, and average RNFL thicknesses (avRNFLT). All ssPERG parameters were significantly correlated with the average and minimum GCL/IPL thicknesses and the inner macular sector thicknesses. Mag and MagD significantly predicted the superior, inferior, and avRNFLT in the regression analysis. All ssPERG parameters were predictive of GCL/IPL thickness in all sectors as well as the average and minimum GCL/IPL thicknesses. All ssPERG parameters were predictive of all inner macular sector thicknesses and MagD was also predictive of some outer macular sector thicknesses as well. Conclusion: ssPERG has significant correlations with and is predictive of RNFL, GCL/IPL, and macular thicknesses in glaucoma suspects. Clinical significance: ssPERG may serve as a useful objective functional tool for identifying and following the progression of disease in glaucoma suspects.

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