The British journal of ophthalmology · 2012
Detection of glaucoma progression by population and individual derived variability criteria.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Folio Lindsey S, Wollstein Gadi, Kotowski Jacek, Bilonick Richard A, Ling Yun, Ishikawa Hiroshi, Kagemann Larry, Schuman Joel S
Аннотация
PURPOSE: Ocular imaging devices provide quantitative structural information that might improve glaucoma progression detection. This study examined scanning laser polarimetry (SLP) population-derived versus individual-derived cut-off criteria for detecting progression.
METHODS: Forty-eight healthy, glaucoma suspect and glaucoma subjects, providing 76 eyes were used. All subjects had reliable visual field (VF) and SLP scans acquired at the same visits from ≥4 visits. VF progression was defined by guided progression analysis (GPA) and by the VF index. SLP measurements were analysed by fast mode (FM) GPA, compared with the population rate of progression, and extended mode (EM) GPA, compared with the individual variability. The agreement between progression detection methods was measured.
RESULTS: Poor agreement was observed between progression defined by VF and FM and EM. The difference in temporal-superior-nasal-inferior-temporal (TSNIT) average rate of change between VF defined progressors and non-progressors for both FM (p=0.010) and EM (p=0.015) was statistically significant.
CONCLUSIONS: There is poor agreement between VF and SLP progression regardless of the use of population derived or individual variability criteria. The best SLP progression detection method could not be ascertained, therefore, acquiring three SLP scans per visit is recommended.
METHODS: Forty-eight healthy, glaucoma suspect and glaucoma subjects, providing 76 eyes were used. All subjects had reliable visual field (VF) and SLP scans acquired at the same visits from ≥4 visits. VF progression was defined by guided progression analysis (GPA) and by the VF index. SLP measurements were analysed by fast mode (FM) GPA, compared with the population rate of progression, and extended mode (EM) GPA, compared with the individual variability. The agreement between progression detection methods was measured.
RESULTS: Poor agreement was observed between progression defined by VF and FM and EM. The difference in temporal-superior-nasal-inferior-temporal (TSNIT) average rate of change between VF defined progressors and non-progressors for both FM (p=0.010) and EM (p=0.015) was statistically significant.
CONCLUSIONS: There is poor agreement between VF and SLP progression regardless of the use of population derived or individual variability criteria. The best SLP progression detection method could not be ascertained, therefore, acquiring three SLP scans per visit is recommended.