Glaucoma Division, Wilmer Eye Institute, Johns Hopkins University, Baltimore, Maryland, USA.
Ophthalmology. 2011 May;118(5):986-1002. doi: 10.1016/j.ophtha.2011.03.019.
To review the published literature to summarize and evaluate the effectiveness of visual function tests in diagnosing glaucoma and in monitoring progression.
Literature searches of the PubMed and Cochrane Library databases were conducted last on May 7, 2010, and were restricted to citations published on or after January 1, 1994. The search yielded 1063 unique citations. The first author reviewed the titles and abstracts of these articles and selected 185 of possible clinical relevance for further review. The panel members reviewed the full text of these articles and determined that 85 met inclusion criteria. They conducted data abstraction of the 85 studies, and the panel methodologist assigned a level of evidence to each of the selected articles. One study was rated as level I evidence. The remaining articles were classified broadly as providing level II evidence. Studies deemed to provide level III evidence were not included in the assessment.
Standard white-on-white automated perimetry remains the most commonly performed test for assessing the visual field, with the Swedish interactive threshold algorithm (SITA) largely replacing full-threshold testing strategies. Frequency-doubling technology and its refinement into Matrix perimetry, as well as short-wavelength automated perimetry, now available with SITA, have been evaluated extensively. Machine learning classifiers seem to be ready for incorporation into software to help distinguish glaucomatous from nonglaucomatous fields. Other technologies, such as multifocal visual-evoked potential and electroretinography, which were designed as objective measures of visual function, provide testing free of patient input, but issues prevent their adoption for glaucoma management.
Advances in technology and analytic tools over the past decade have provided us with more rapid and varied ways of assessing visual function in glaucoma, but they have yet to produce definitive guidance on the diagnosis of glaucoma or its progression over time. Further research on an objective measure of visual function is needed.
回顾已发表的文献，总结和评估视觉功能测试在诊断青光眼和监测疾病进展方面的有效性。
于 2010 年 5 月 7 日对 PubMed 和 Cochrane Library 数据库进行文献检索，检索时间限定为 1994 年 1 月 1 日以后发表的文献。共检索到 1063 篇文献。第一作者首先浏览了这些文章的标题和摘要，选择了 185 篇可能与临床相关的文章进行进一步评估。专家组对这些文章的全文进行了评估，确定其中 85 篇符合纳入标准。他们对这 85 项研究进行了数据提取，专家组方法学家对入选的每篇文章进行了证据分级。其中有 1 项研究被评为 I 级证据，其余文章则被归类为 II 级证据。未将被认为提供 III 级证据的研究纳入评估。
标准的白到白自动视野计仍然是最常用于评估视野的检查方法，其中瑞典交互阈值算法（SITA）在很大程度上取代了全阈值测试策略。频域技术及其在 Matrix 视野计中的发展，以及短波长自动视野计，现在与 SITA 一起使用，已经得到了广泛的评估。机器学习分类器似乎已经准备好被纳入软件，以帮助区分青光眼和非青光眼视野。其他技术，如多焦视觉诱发电位和视网膜电图，旨在作为视觉功能的客观测量方法，提供无需患者输入的测试，但由于存在问题而无法用于青光眼的管理。
过去十年中，技术和分析工具的进步为我们提供了更快速和多样化的评估青光眼患者视觉功能的方法，但它们尚未就青光眼的诊断或随时间推移的疾病进展提供明确的指导。需要进一步研究客观的视觉功能测量方法。
