Consensus Nomenclature for Reporting Neovascular Age-Related Macular Degeneration Data
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1-s2.0-S0161642019322432-main.pdf
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Published version
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9.97 MB
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Author(s) • • • • • • • • •
Spaide, Richard F.
Jaffe, Glenn J.
Sarraf, David
Freund, K. Bailey
Sadda, Srinivas R.
Staurenghi, Giovanni
Waheed, Nadia K.
Chakravarthy, Usha
Rosenfeld, Philip J.
Holz, Frank G.
Date Issued
May 2020
Journal
Ophthalmology
Publisher
Elsevier BV
Citation
Spaide, Richard F. et al. "Consensus Nomenclature for Reporting Neovascular Age-Related Macular Degeneration Data." 127, 5 (May 2020): P616-636 © 2019 American Academy of Ophthalmology
Version
Final published version
Abstract
Purpose: To establish a process to evaluate and standardize a state-of-the-art nomenclature for reporting neovascular age-related macular degeneration (AMD) data. Design: Consensus meeting. Participants: An international panel of retina specialists, imaging and image reading center experts, and ocular pathologists. Methods: During several meetings organized under the auspices of the Macula Society, an international study group discussed and codified a set nomenclature framework for classifying the subtypes of neovascular AMD and associated lesion components. Main Outcome Measures: A consensus classification of neovascular AMD. Results: The study group created a standardized working definition of AMD. The components of neovascular AMD were defined and subclassified. Disease consequences of macular neovascularization were delineated. Conclusions: The framework of a consensus nomenclature system, a definition of AMD, and a delineation of the subtypes of neovascular AMD were developed. Establishing a uniform set of definitions will facilitate comparison of diverse patient groups and different studies. The framework presented is modified and updated readily, processes that are anticipated to occur on a periodic basis. The study group suggests that the consensus standards outlined in this article be used in future reported studies of neovascular AMD and clinical practice.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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DOI of Published Version
https://doi.org/10.1016/j.ophtha.2019.11.004