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A meta-analysis of clinical electro-oculography values
Paul A Constable1, David Ngo2, Stephen Quinn3
1College of Nursing and Health Sciences, Flinders University, GPO Box 2100, Adelaide, SA, 5001, Australia. Paul.Constable@flinders.edu.au.
Documenta Ophthalmologica. Advances in Ophthalmology
|October 12, 2017
Summary
This meta-analysis provides normal clinical electrooculogram (EOG) values for clinicians. It establishes reference ranges for light peak/dark trough ratio (LP:DT ratio) and other EOG parameters based on ISCEV standards.
Area of Science:
- Ophthalmology
- Neuroscience
- Clinical Electrophysiology
Background:
- The electrooculogram (EOG) is a key clinical test in visual electrophysiology.
- Standardized normal values are essential for accurate EOG interpretation.
- Existing EOG studies vary in methodology, necessitating a consolidated reference range.
Purpose of the Study:
- To systematically review published electrooculogram (EOG) studies.
- To derive a comprehensive range of mean normal clinical EOG values.
- To establish reference data adhering to International Society for Clinical Electrophysiology of Vision (ISCEV) standards.
Main Methods:
- A systematic literature review of EOG studies published between 1967 and February 2017 was conducted.
- Nine peer-reviewed articles meeting ISCEV standard criteria (30° saccade, specific luminance, >10 subjects) were included.
- Inverse variance-weighted meta-analysis was used to calculate mean values for key EOG parameters.
Main Results:
- Mean light peak/dark trough (LP:DT) ratios were derived: 2.35 (dilated) and 2.37 (undilated).
- Mean amplitudes for light peak (LP) and dark trough (DT) were 835 µV and 358 µV, respectively.
- Mean time to LP was 8.2 min, and the mean fast oscillation (FO) peak-to-trough ratio was 1.13.
Conclusions:
- This meta-analysis successfully generated a reference range of normal mean electrooculogram (EOG) values.
- The derived values provide a valuable resource for clinicians using the ISCEV standard for EOG.
- This methodology can be applied to create similar datasets for other visual electrophysiology tests.

