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Volume 2012 (2012), Article ID 127562, 6 pages
Research Article

Large-Scale Survey of Unselected Automated Visual Fields in a Major Reading Center: Patterns and Data Analysis

1Deptartment of Ophthalmology, MOR Institute for Medical Data, 51108 Bnei Brak, Israel
2Department of Ophthalmology, Wolfson Medical Center, 58100 Holon, Israel
3Department of Ophthalmology, Rabin Medical Center, Beilinson Hospital, 49100 Petach Tikva, Israel
4Sackler Faculty of Medicine, Tel Aviv University, 69978 Tel Aviv, Israel
5Department of Epidemiology, Wolfson Medical Center, 58100 Holon, Israel

Received 20 March 2012; Accepted 9 May 2012

Academic Editors: R. Kröger and H. Noma

Copyright © 2012 Lilly Zborowski-Naveh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A prospective, randomized study was conducted to survey a large number of automated perimetry examinations in a central reading institute, obtaining practical information on unselected referred patients and their clinician “consumers”. Visual field records of 1041 patients were obtained, each evaluated by one of three glaucoma specialists. Statistical analysis was applied on demographics, physician characteristics, test reliability and visual field scores. Reliability was scored on a scale of 1 (excellent) to 5 (uninterpretable). Data from earlier examinations of these patients was also analyzed. The large majority of patients (70.4%) were referred due to glaucoma, ocular hypertension or suspected glaucoma. Most of the patients had threshold strategies: FastPac 24-2 or 30-2 (88.9%), Full Threshold (0.7%), and 10-2 (0.5%). In only 7 patients was short-wavelength automated perimetry (SWAP) performed. The Swedish Interactive Testing Algorithm (SITA) was applied in 1.0% of cases. More than half (56.8%) of the population had a reliability score of 1, and 22.7% had a score of 2, indicating a valid result for 79.4% of patients, providing clinically useful information. Linear regression analyses indicated that the Mean Defect was a better predictor of the visual field score than the Corrected Pattern Standard Deviation (CPSD), for the entire group and for each visual field score subgroup.