Optimum criteria for short-wavelength automated perimetry.

Abstract

To determine the optimum perimetric criteria for short-wavelength automated perimetry on the basis of probabilistic maps that best discriminate between normal and glaucoma. Comparative cross-sectional study. Ninety-five glaucomatous eyes and 128 normal eyes were included in the study. The subjects underwent retinal nerve fiber layer photographic evaluation and short-wavelength automated perimetry. A probabilistic map of differential points for short-wavelength automated perimetry was elaborated, and the number of altered points was calculated for each visual field and level of significance (95%, 98%, 99%, and 99.5%). The presence of a cluster of four or more points outside 95% normal probability limit showed a good combination of sensitivity and specificity. At deeper levels, P: < 1% and P: < 0.5%, the best combination is achieved with three points outside the normal probability limits. The optimum criterion to define glaucomatous abnormalities in short-wavelength automated perimetry is the presence of a cluster of four points lower than P: < 5% or a cluster of three points lower than P: < 1%.