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

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 evalua...

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Detalles Bibliográficos
Autores principales: Zborowski-Naveh, Lilly, Ehrlich, Rita, Luski, Moshe, Weinberger, Dov, Boaz, Mona, Gaton, Dan D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3820557/
https://www.ncbi.nlm.nih.gov/pubmed/24278666
http://dx.doi.org/10.6064/2012/127562
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author Zborowski-Naveh, Lilly
Ehrlich, Rita
Luski, Moshe
Weinberger, Dov
Boaz, Mona
Gaton, Dan D.
author_facet Zborowski-Naveh, Lilly
Ehrlich, Rita
Luski, Moshe
Weinberger, Dov
Boaz, Mona
Gaton, Dan D.
author_sort Zborowski-Naveh, Lilly
collection PubMed
description 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.
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spelling pubmed-38205572013-11-25 Large-Scale Survey of Unselected Automated Visual Fields in a Major Reading Center: Patterns and Data Analysis Zborowski-Naveh, Lilly Ehrlich, Rita Luski, Moshe Weinberger, Dov Boaz, Mona Gaton, Dan D. Scientifica (Cairo) Research Article 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. Hindawi Publishing Corporation 2012 2012-05-20 /pmc/articles/PMC3820557/ /pubmed/24278666 http://dx.doi.org/10.6064/2012/127562 Text en Copyright © 2012 Lilly Zborowski-Naveh et al. https://creativecommons.org/licenses/by/3.0/ 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.
spellingShingle Research Article
Zborowski-Naveh, Lilly
Ehrlich, Rita
Luski, Moshe
Weinberger, Dov
Boaz, Mona
Gaton, Dan D.
Large-Scale Survey of Unselected Automated Visual Fields in a Major Reading Center: Patterns and Data Analysis
title Large-Scale Survey of Unselected Automated Visual Fields in a Major Reading Center: Patterns and Data Analysis
title_full Large-Scale Survey of Unselected Automated Visual Fields in a Major Reading Center: Patterns and Data Analysis
title_fullStr Large-Scale Survey of Unselected Automated Visual Fields in a Major Reading Center: Patterns and Data Analysis
title_full_unstemmed Large-Scale Survey of Unselected Automated Visual Fields in a Major Reading Center: Patterns and Data Analysis
title_short Large-Scale Survey of Unselected Automated Visual Fields in a Major Reading Center: Patterns and Data Analysis
title_sort large-scale survey of unselected automated visual fields in a major reading center: patterns and data analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3820557/
https://www.ncbi.nlm.nih.gov/pubmed/24278666
http://dx.doi.org/10.6064/2012/127562
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