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G. Takahashi, S. Demirel, C.A. Johnson; Predicting Glaucomatous Visual Field Loss Using Short Wavelength Automated Perimetry . Invest. Ophthalmol. Vis. Sci. 2003;44(13):59.
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© ARVO (1962-2015); The Authors (2016-present)
Purpose: To investigate the ability of Short Wavelength Automated Perimetry (SWAP) to predict the onset of glaucomatous field loss defined using Standard Automated Perimetry (SAP). Methods: One-hundred and sixty-two eyes that either had glaucomatous optic neuropathy (GON; n=47), were suspect for glaucoma (Suspect; n=60) or who had perimetrically early glaucoma (EG) were enrolled in a prospective, longitudinal study. Eyes in the GON and Suspect groups all had SAP results that were within normal limits at the initial visit. Eyes with early glaucomatous visual field loss had MD values (SAP) ranging from -10.3 to 1.61 dB.Visual fields were assessed on an annual basis using SAP and SWAP. An eye was deemed to have ‘converted’ if the SAP glaucoma hemifield test (GHT) became ‘outside normal limits’ or the SAP pattern standard deviation (PSD) probability fell outside the lower 5th normal percentile or if at least three clustered points at or outside the 5th normal percentile were present on the SAP pattern deviation (PD) probability plot. We also evaluated an additional scenario in which a confirmatory abnormal field was required before an eye was classified as converted. Results: A form of multivariate modeling (Classification and Regression Tree, CART) revealed that sensitivity of SWAP for predicting future SAP damage ranged between 37.9 and 85.7% whereas specificity ranged between 44 and 88.5% depending on the number of years of data admitted to the model and the criterion for conversion that was employed. This level of performance could be obtained frequently using decision rules based on only a few variables. Conclusions: Results produced by both SWAP and SAP have predictive capacity for future glaucomatous visual field loss as determined by SAP. The predictive ability of SWAP for SAP abnormality emerges at an earlier time point than if SAP results are used to predict SAP abnormality. Interestingly, significant predictive capacity exists when visual field indices are still within statistically normal limits.
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