title: Diagnostic accuracy of pattern electroretinogram optimized for glaucoma detection.
abstract: OBJECTIVE
  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).
  
  
  METHODS
  Cross-sectional study.
  
  
  METHODS
  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).
  
  
  METHODS
  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.
authors.affiliation: Hamilton Glaucoma Center and Department of Ophthalmology, University of California, San Diego, La Jolla, California 92037-0946, USA. cbowd@eyecenter.ucsd.edu
authors.forename: Christopher
authors.initials: C
authors.lastname: Bowd
authors.forename: Gianmarco
authors.initials: G
authors.lastname: Vizzeri
authors.forename: Ali
authors.initials: A
authors.lastname: Tafreshi
authors.forename: Linda M
authors.initials: LM
authors.lastname: Zangwill
authors.forename: Pamela A
authors.initials: PA
authors.lastname: Sample
authors.forename: Robert N
authors.initials: RN
authors.lastname: Weinreb
mesh_terms: D000368:Aged; D019540:Area Under Curve; D003430:Cross-Sectional Studies; D004596:Electroretinography / Q000592:standards*; D005188:False Negative Reactions; D005260:Female; D005902:Glaucoma, Open-Angle / Q000175:diagnosis*; D006801:Humans; D007429:Intraocular Pressure; D008297:Male; D008875:Middle Aged; D009898:Optic Disk / Q000473:pathology*; D009901:Optic Nerve Diseases / Q000175:diagnosis*; D010781:Photography; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D058609:Visual Field Tests; D014794:Visual Fields