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A specific, sensitive and intersubjectively verifiable definition of disease for clinical care and research remains an important unmet need in the field of glaucoma. Using an iterative, consensus-building approach and employing pilot data, an optical coherence tomography (OCT)-based method to aid in the detection of glaucomatous optic neuropathy was sought to address this challenge. To maximize the chance of success, we utilized all available information from the OCT circle and cube scans, applied both quantitative and semi-quantitative data analysis methods, and aimed to limit the use of perimetry to cases where it is absolutely necessary. The outcome of this approach was an OCT-based method for diagnosis of glaucomatous optic neuropathy that did not require the use of perimetry for initial diagnosis. A decision-tree was devised for testing and implementation in clinical practice and research that can be used by reading centers, researchers, and clinicians. While intial pilot data were encouraging, future testing and validation will be needed to establish its utility in clinical practice, as well as for research.
Bernard and Shirlee Brown Glaucoma Research Laboratory, Edward S. Harkness Eye Institute, Department of Ophthalmology, Columbia University Irving Medical Center, 635 W 165th St, New York, NY, USA 10032 Department of Psychology, Columbia University Schermerhorn Hall, 1190 Amsterdam Ave #406, New York, NY, USA 10027.
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