MISC

1999年4月

Indocyanine green angiographic features prognostic of visual outcome in the natural course of patients with age related macular degeneration

BRITISH JOURNAL OF OPHTHALMOLOGY
  • A Obana
  • ,
  • Y Gohto
  • ,
  • M Matsumoto
  • ,
  • T Miki
  • ,
  • K Nishiguti

83
4
開始ページ
429
終了ページ
437
記述言語
英語
掲載種別
出版者・発行元
BRITISH MED JOURNAL PUBL GROUP

Aims-To determine indocyanine green (ICG) angiographic features prognostic of visual acuity loss in eyes following a natural course of exudative age related macular degeneration (AMD).
Methods-89 eyes of 72 patients (48 men, 24 women) aged between 50 and 87 years old (mean 69.5 (SD 8.8) years) with classic and/or occult choroidal neovascularisation (CNV) were reviewed. ICG angiographic features were classified as follows: type 1, well demarcated hyperfluorescence with late ICG leakage; type 2, well demarcated hyperfluorescence with no late dye leakage; type 3, poorly demarcated hyperfluorescence; type 4, no hyperfluorescence. Follow up ranged from 6 to 67 months (mean 19.2 (11.5) months). Logistic regression analyses were performed using change of visual acuity (worse or not) as the dependent variable, and patient age, sex, characteristics of fluorescein angiography (classic or occult CNV), location of CNV, and each ICG type as the independent variables. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated.
Results-Type 1 CNV was associated with the highest risk for visual acuity loss (OR: 7.50, CI: 1.42-39.55, p = 0.018) among the present variables. In contrast, CNV having no ICG leakage (type 2, 3, and 4), represented no significantly increased risk.
Conclusion-Well demarcated hyperfluorescence with late ICG leakage appears to be predictive of visual acuity loss in eyes with CNV. Thus, ICG angiography may offer a useful means of predicting visual outcomes in AMD.

リンク情報
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000079644400020&DestApp=WOS_CPL
ID情報
  • ISSN : 0007-1161
  • Web of Science ID : WOS:000079644400020

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