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Development of an LCD-Based Visual Field System
Journal of Korean Medical Science ; : e19-2018.
Article in English | WPRIM | ID: wpr-764864
ABSTRACT

BACKGROUND:

The present study investigated the diagnostic effectiveness of an LCD-based visual field testing system (LVF) in comparison with the standard automated perimetry Humphrey Field Analyzer II-750i (HFA).

METHODS:

A randomized controlled crossover study was conducted with 202 normal and 128 glaucomatous eyes using both LVF and HFA. The visual field testing systems were compared in terms of mean deviation (MD), pattern standard deviation (PSD), and area under the receiver operating characteristics curve (AUC) of MD and PSD differentiating the normal and glaucomatous eyes.

RESULTS:

Significant correlations were found between MD measurements from LVF and those from HFA for normal eyes (r = 0.342) and glaucomatous eyes (r = 0.796); slightly higher significant correlations were identified between PSD measurements from LVF and those from HFA for normal eyes (r = 0.363) and glaucomatous eyes (r = 0.828). Furthermore, high AUCs of MD were found as 0.786 for LVF and 0.868 for HFA and AUCs of PSD as 0.913 for LVF and 0.932 for HFA.

CONCLUSION:

The comparison results of the present study support the competence of LVF compared with HFA in visual field testing for early detection of glaucoma.
Subject(s)

Full text: Available Index: WPRIM (Western Pacific) Main subject: Visual Fields / Glaucoma / ROC Curve / Mental Competency / Cross-Over Studies / Area Under Curve / Visual Field Tests Type of study: Controlled clinical trial / Prognostic study / Screening study Language: English Journal: Journal of Korean Medical Science Year: 2018 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Visual Fields / Glaucoma / ROC Curve / Mental Competency / Cross-Over Studies / Area Under Curve / Visual Field Tests Type of study: Controlled clinical trial / Prognostic study / Screening study Language: English Journal: Journal of Korean Medical Science Year: 2018 Type: Article