Advantages of Terminating Zippy Estimation by Sequential Testing (ZEST) With Dynamic Criteria for White-on-White Perimetry

Purpose. Several current perimetric test strategies use information from neighboring test locations to seed the procedure. When this initial estimate is close to the true threshold, the algorithms terminate quickly with low error. However, when neighboring thresholds are dissimilar, seeding procedures in this manner results in poor accuracy and repeatability. This study aims to develop a test procedure that avoids assumptions based on neighboring locations yet terminates with an acceptable number of presentations. We explore the utility of a combined screening and threshold approach. Methods. Our approach [estimation minimizing uncertainty (EMU)] first applies suprathreshold screening and then in those locations that fail the screening, a ZEST procedure commencing with a uniform probability density function (pdf). EMU was compared with full threshold (FT) using computer simulation. Input to the simulation was empirical standard automated perimetry data (FT) from 265 normal subjects and 163 observers with glaucomatous visual field loss. Test performance was assessed using four patient error models designed to represent patients who respond with no errors, typical false-positive errors, typical false-negative errors, and extremely unreliable patients. Results. When patients made typical false-positive errors, EMU required about 20% fewer presentations than FT averaged across the visual field. EMU required a greater number of presentations than FT when false-negative errors were made. The percentage of locations misclassified as either normal (defined as the thresholds greater than the lower 95% confidence limit of age-corrected norms) or abnormal by EMU was lower than for FT.