Variability and Errors of Manually Digitized Goldmann Visual Fields

手动数字化Goldmann视野的变异性和误差

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Abstract

PURPOSE: Goldmann visual fields (GVFs) are useful for tracking changes in areas of functional retina, including the periphery, in inherited retinal degeneration patients. Quantitative GVF analysis requires digitization of the chart coordinates for the main axes and isopter points marked by the GVF operator during testing. This study investigated inter- and intra-digitizer variability among users of a manual GVF digitization program. METHODS: Ten digitizers were trained for 1 hour, then digitized 23 different GVFs from inherited retinal degeneration patients in each of three testing blocks. Digitizers labeled each isopter as seeing or non-seeing, and its target size. Isopters with the same test target within each GVF were grouped to create isopter groups. RESULTS: The standard deviation of isopter group area showed an approximate square-root relationship with total isopter group area. Accordingly, the coefficient of variation for isopter group area decreased from 68% to 0.2% with increasing isopter group area. A bootstrap version of ANOVA did not reveal a significant effect of digitizers on isopter group area. Simulations involving random sampling of digitizers showed that five to seven digitizers would be required to catch 95% to 99% of labeling errors and isopter misses, on the basis of data discrepancies, with 99% probability. CONCLUSIONS: These data suggest that any minimally trained digitizer would be capable of reliably determining any isopter area, regardless of size. Studies using this software could either use five to seven minimally trained digitizers for each GVF, three digitizers who demonstrate low frequencies of errors on a practice set of GVFs, or two digitizers with an expert reader to adjudicate discrepancies and catch errors.

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