advertisement
Abstract #9756 Published in IGR 5-3
Anatomy of a supergroup: does a criterion of normal perimetric performance generate a supernormal population?
Anderson AJ; Johnson CAInvestigative Ophthalmology and Visual Science 2003; 44: 5043-5048
PURPOSE: To interpret individual results from automated perimeters, a normative database must be developed. Typically, a set of criteria determines those subjects that may be included in the database. This study examined whether a criterion of normal performance on an established perimeter generates a subgroup with supernormal perimetric performance. METHODS: The right-eye perimetric results of 100 subjects were analyzed. Subjects had visual acuities of 6/12 or better, no history of eye disease, and normal slit lamp biomicroscopic and ophthalmoscopic examinations. Subjects performed test-retest visual field examinations on a Humphrey Field Analyzer (HFA) 24-2 test (Zeiss Humphrey Systems, Dublin, CA), and on a custom frequency-doubling (FD) perimeter with targets spaced in the same 24-2 pattern. RESULTS: Test-retest correlation (Spearman rank correlation coefficients, rs) for mean defect (MD) and pattern SD (PSD) were 0.65 and 0.40 (HFA), and 0.82 and 0.39 (FD perimeter). Three subjects with HFA MDs in the lower 5% had similarly low MDs on retest, whereas no subject was common between the test and retest for the lower 5% of HFA PSD. Correlation between the HFA and FD test results were 0.41 (MD) and 0.05 (PSD). Based on these correlations, the bias introduced into perimetric probability limits were determined, by using Monte Carlo simulations. CONCLUSIONS: Although a criterion of a normal MD may produce a subpopulation with supernormal perimetric performance, a criterion of a normal PSD is less likely to do so. Also, a criterion on one test type is less likely to create a supernormal group on a different test type. The bias introduced into perimetric probability limits is small.
Dr. A.J. Anderson, Discoveries in Sight, Devers Eye Institute, Portland, OR 97232, USA
Classification:
6.6.2 Automated (Part of: 6 Clinical examination methods > 6.6 Visual field examination and other visual function tests)
