Purpose: To assess the ability of the new pattern electroretinogram optimized for glaucoma detection (PERGLA) paradigm to discriminate between healthy individuals and individuals with glaucomatous optic neuropathy (GON).
Design: Cross-sectional study.
Participants: One hundred forty-two eyes of 71 participants (42 healthy and 29 with GON in at least 1 eye) enrolled in the University of California, San Diego, Diagnostic Innovations in Glaucoma Study were studied. Healthy individuals were those recruited as healthy with healthy-appearing optic disc by examination and masked stereoscopic optic disc photograph evaluation. Glaucomatous optic neuropathy was defined based on stereophotograph evaluation.
Methods: The PERGLA (Glaid Elettronica, Pisa, Italy) recordings were obtained within 6 months of standard automated perimetry (SAP) testing. Dependent variables were PERGLA amplitude, phase, amplitude asymmetry, phase asymmetry, and SAP pattern standard deviation (PSD) and mean deviation (MD).
Main outcome measures: Diagnostic accuracy (sensitivity and specificity) of the PERGLA normative database for classifying healthy and glaucomatous individuals was determined. In addition, performance (areas under receiver operating characteristic curves [AUCs]) of PERGLA amplitude and phase for classifying healthy (n=84) and GON (n=50) eyes was determined. Results from both analyses were compared with those from SAP.
Results: Sensitivity and specificity of the PERGLA normative database were 0.76 and 0.59, respectively, compared with 0.83 and 0.77 for SAP. The AUCs for PERGLA amplitude and phase were 0.75 and 0.50 (chance performance), respectively. The AUCs for SAP PSD and MD were 0.83 and 0.78, respectively.
Conclusions: Pattern electroretinograms recorded using the PERGLA paradigm can discriminate between healthy and glaucoma eyes, although this technique performed no better than SAP at this task. Low specificity of the PERGLA normative database suggests that the distribution of recordings included in the database is not ideal.