Predicting Progression to Glaucoma in Ocular Hypertensive Patients

PURPOSETo assess the ability of Heidelberg Retina Tomograph (HRT) Moorfields Regression Analysis (MRA) and Glaucoma Probability Score (GPS) classifications at baseline to predict glaucomatous progression in ocular hypertensive eyes. METHODSOne hundred ninety-eight ocular hypertensive subjects underw...

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Veröffentlicht in:Journal of glaucoma 2010-06, Vol.19 (5), p.304-309
Hauptverfasser: Strouthidis, Nicholas G, Gardiner, Stuart K, Owen, Victoria M.F, Zuniga, Claudio, Garway-Heath, David F
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Sprache:eng
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Zusammenfassung:PURPOSETo assess the ability of Heidelberg Retina Tomograph (HRT) Moorfields Regression Analysis (MRA) and Glaucoma Probability Score (GPS) classifications at baseline to predict glaucomatous progression in ocular hypertensive eyes. METHODSOne hundred ninety-eight ocular hypertensive subjects underwent regular HRT and visual field (VF) testing from 1993 to 2001. HRT progression was assessed using linear regression of rim area/time. VF progression was assessed by pointwise linear regression of sensitivity/time. Subjects were classified as progressing or stable at the end of the study period. The relationship between baseline abnormal (outside normal limits combined with borderline classification) MRA and GPS classification and progression status was assessed by odds ratios (ORs). RESULTSAn abnormal superotemporal MRA was the only classification found to be predictive of HRT progression in isolation (OR 3.05, 1.25-7.47). Abnormal global, superotemporal, superonasal, and temporal MRA classifications were all associated with significant ORs for predicting HRT or VF progression (OR range1.77-2.54). Abnormal GPS classifications were not predictive of disease behavior. Combined abnormal GPS and MRA classifications were associated with higher ORs than either classification in isolation. CONCLUSIONSPatients with an abnormal MRA and GPS classification at presentation may be at increased risk of HRT or VF change.
ISSN:1057-0829
1536-481X
DOI:10.1097/IJG.0b013e3181b6e5a1