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Paul H. Artes, David B. Henson, Robert Harper, David McLeod; Multisampling Suprathreshold Perimetry: A Comparison with Conventional Suprathreshold and Full-Threshold Strategies by Computer Simulation. Invest. Ophthalmol. Vis. Sci. 2003;44(6):2582-2587. doi: 10.1167/iovs.02-1036.
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purpose. To compare a multisampling suprathreshold strategy with conventional suprathreshold and full-threshold strategies in detecting localized visual field defects and in quantifying the area of loss.
methods. Probability theory was applied to examine various suprathreshold pass criteria (i.e., the number of stimuli that have to be seen for a test location to be classified as normal). A suprathreshold strategy that requires three seen or three missed stimuli per test location (multisampling suprathreshold) was selected for further investigation. Simulation was used to determine how the multisampling suprathreshold, conventional suprathreshold, and full-threshold strategies detect localized field loss. To determine the systematic error and variability in estimates of loss area, artificial fields were generated with clustered defects (0–25 field locations with 8- and 16-dB loss) and, for each condition, the number of test locations classified as defective (suprathreshold strategies) and with pattern deviation probability less than 5% (full-threshold strategy), was derived from 1000 simulated test results.
results. The full-threshold and multisampling suprathreshold strategies had similar sensitivity to field loss. Both detected defects earlier than the conventional suprathreshold strategy. The pattern deviation probability analyses of full-threshold results underestimated the area of field loss. The conventional suprathreshold perimetry also underestimated the defect area. With multisampling suprathreshold perimetry, the estimates of defect area were less variable and exhibited lower systematic error.
conclusions. Multisampling suprathreshold paradigms may be a powerful alternative to other strategies of visual field testing. Clinical trials are needed to verify these findings.
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