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Nicholas G. Strouthidis, Andrew Scott, Ananth C. Viswanathan, David P. Crabb, David F. Garway-Heath; Monitoring Glaucomatous Visual Field Progression: The Effect of a Novel Spatial Filter. Invest. Ophthalmol. Vis. Sci. 2007;48(1):251-257. doi: 10.1167/iovs.06-0576.
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purpose. To assess the impact of a novel visual field spatial filtering technique on the detection of glaucomatous progression.
methods. One hundred ninety-eight ocular hypertensive (OHT) and 21 control subjects were examined prospectively (1994–2001) with regular full-threshold Humphrey visual field (VF) testing. VF progression was assessed by point-wise linear regression (PLR) of sensitivity/time in Progressor for Windows software modified to include a novel spatial filter. Standard progression criteria (slope > −1 dB/year, P < 0.01) were applied to both “raw” (unfiltered) and “filtered” VF series. Three-omitting confirmatory VF criteria were also applied to unfiltered VF series. Specificity was estimated as the proportion of progressing control subjects and as the proportion of significantly improving subjects (both OHT and control) at the end of the study period.
results. Applying standard PLR, specificity was estimated at 91.8% to 97.5% using unfiltered standard PLR, compared with 93.5% to 98.4% using filtered standard PLR and 95.4% to 99.3% using unfiltered three-omitting PLR. The rate of identified VF progression in the OHT cohort was 32.3% with unfiltered standard PLR, 28.7% with filtered standard PLR, and 18.6% with unfiltered three-omitting PLR. There was no significant difference in time to detected progression between filtered and unfiltered standard PLR.
conclusions. The use of confirmatory tests resulted in improved specificity using unfiltered data; however, application of the spatial filter resulted in similar specificity but with a higher rate of detected progression. This filter may therefore be useful in the monitoring of glaucomatous progression as it may reduce the dependence on confirmatory testing, although it has yet to be applied to longitudinal SITA data.
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