Diagnostic Accuracy of Pattern Electroretinogram Optimized for Glaucoma Detection

Christopher Bowd, Gianmarco Vizzeri, Ali Tafreshi, Linda M. Zangwill, Pamela A. Sample, Robert N. Weinreb

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

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. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.

Original languageEnglish (US)
Pages (from-to)437-443
Number of pages7
JournalOphthalmology
Volume116
Issue number3
DOIs
StatePublished - Mar 2009
Externally publishedYes

Fingerprint

Glaucoma
Visual Field Tests
Optic Nerve Diseases
Databases
Area Under Curve
Optic Disk
Disclosure
Sensitivity and Specificity
ROC Curve
Italy
Healthy Volunteers
Cross-Sectional Studies
Outcome Assessment (Health Care)

ASJC Scopus subject areas

  • Ophthalmology

Cite this

Bowd, C., Vizzeri, G., Tafreshi, A., Zangwill, L. M., Sample, P. A., & Weinreb, R. N. (2009). Diagnostic Accuracy of Pattern Electroretinogram Optimized for Glaucoma Detection. Ophthalmology, 116(3), 437-443. https://doi.org/10.1016/j.ophtha.2008.10.026

Diagnostic Accuracy of Pattern Electroretinogram Optimized for Glaucoma Detection. / Bowd, Christopher; Vizzeri, Gianmarco; Tafreshi, Ali; Zangwill, Linda M.; Sample, Pamela A.; Weinreb, Robert N.

In: Ophthalmology, Vol. 116, No. 3, 03.2009, p. 437-443.

Research output: Contribution to journalArticle

Bowd, C, Vizzeri, G, Tafreshi, A, Zangwill, LM, Sample, PA & Weinreb, RN 2009, 'Diagnostic Accuracy of Pattern Electroretinogram Optimized for Glaucoma Detection', Ophthalmology, vol. 116, no. 3, pp. 437-443. https://doi.org/10.1016/j.ophtha.2008.10.026
Bowd, Christopher ; Vizzeri, Gianmarco ; Tafreshi, Ali ; Zangwill, Linda M. ; Sample, Pamela A. ; Weinreb, Robert N. / Diagnostic Accuracy of Pattern Electroretinogram Optimized for Glaucoma Detection. In: Ophthalmology. 2009 ; Vol. 116, No. 3. pp. 437-443.
@article{0ed4e151c1b840159ac9071e85d04421,
title = "Diagnostic Accuracy of Pattern Electroretinogram Optimized for Glaucoma Detection",
abstract = "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. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.",
author = "Christopher Bowd and Gianmarco Vizzeri and Ali Tafreshi and Zangwill, {Linda M.} and Sample, {Pamela A.} and Weinreb, {Robert N.}",
year = "2009",
month = "3",
doi = "10.1016/j.ophtha.2008.10.026",
language = "English (US)",
volume = "116",
pages = "437--443",
journal = "Ophthalmology",
issn = "0161-6420",
publisher = "Elsevier Inc.",
number = "3",

}

TY - JOUR

T1 - Diagnostic Accuracy of Pattern Electroretinogram Optimized for Glaucoma Detection

AU - Bowd, Christopher

AU - Vizzeri, Gianmarco

AU - Tafreshi, Ali

AU - Zangwill, Linda M.

AU - Sample, Pamela A.

AU - Weinreb, Robert N.

PY - 2009/3

Y1 - 2009/3

N2 - 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. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.

AB - 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. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.

UR - http://www.scopus.com/inward/record.url?scp=61349118613&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=61349118613&partnerID=8YFLogxK

U2 - 10.1016/j.ophtha.2008.10.026

DO - 10.1016/j.ophtha.2008.10.026

M3 - Article

VL - 116

SP - 437

EP - 443

JO - Ophthalmology

JF - Ophthalmology

SN - 0161-6420

IS - 3

ER -