Identifying areas of the visual field important for quality of life in patients with glaucoma.

The purpose of this study was to create a vision-related quality of life (VRQoL) prediction system to identify visual field (VF) test points associated with decreased VRQoL in patients with glaucoma.VRQoL score was surveyed in 164 patients with glaucoma using the 'Sumi questionnaire'. A bi...

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Main Authors: Hiroshi Murata, Hiroyo Hirasawa, Yuka Aoyama, Kenji Sugisaki, Makoto Araie, Chihiro Mayama, Makoto Aihara, Ryo Asaoka
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3592814?pdf=render
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author Hiroshi Murata
Hiroyo Hirasawa
Yuka Aoyama
Kenji Sugisaki
Makoto Araie
Chihiro Mayama
Makoto Aihara
Ryo Asaoka
author_facet Hiroshi Murata
Hiroyo Hirasawa
Yuka Aoyama
Kenji Sugisaki
Makoto Araie
Chihiro Mayama
Makoto Aihara
Ryo Asaoka
author_sort Hiroshi Murata
collection DOAJ
description The purpose of this study was to create a vision-related quality of life (VRQoL) prediction system to identify visual field (VF) test points associated with decreased VRQoL in patients with glaucoma.VRQoL score was surveyed in 164 patients with glaucoma using the 'Sumi questionnaire'. A binocular VF was created from monocular VFs by using the integrated VF (IVF) method. VRQoL score was predicted using the 'Random Forest' method, based on visual acuity (VA) of better and worse eyes (better-eye and worse-eye VA) and total deviation (TD) values from the IVF. For comparison, VRQoL scores were regressed (linear regression) against: (i) mean of TD (IVF MD); (ii) better-eye VA; (iii) worse-eye VA; and (iv) IVF MD and better- and worse-eye VAs. The rank of importance of IVF test points was identified using the Random Forest method.The root mean of squared prediction error associated with the Random Forest method (0.30 to 1.97) was significantly smaller than those with linear regression models (0.34 to 3.38, p<0.05, ten-fold cross validation test). Worse-eye VA was the most important variable in all VRQoL tasks. In general, important VF test points were concentrated along the horizontal meridian. Particular areas of the IVF were important for different tasks: peripheral superior and inferior areas in the left hemifield for the 'letters and sentences' task, peripheral, mid-peripheral and para-central inferior regions for the 'walking' task, the peripheral superior region for the 'going out' task, and a broad scattered area across the IVF for the 'dining' task.The VRQoL prediction model with the Random Forest method enables clinicians to better understand patients' VRQoL based on standard clinical measurements of VA and VF.
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spelling doaj.art-fe1275f0e61c4dd681d4e177a956bbd92022-12-21T18:15:36ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0183e5869510.1371/journal.pone.0058695Identifying areas of the visual field important for quality of life in patients with glaucoma.Hiroshi MurataHiroyo HirasawaYuka AoyamaKenji SugisakiMakoto AraieChihiro MayamaMakoto AiharaRyo AsaokaThe purpose of this study was to create a vision-related quality of life (VRQoL) prediction system to identify visual field (VF) test points associated with decreased VRQoL in patients with glaucoma.VRQoL score was surveyed in 164 patients with glaucoma using the 'Sumi questionnaire'. A binocular VF was created from monocular VFs by using the integrated VF (IVF) method. VRQoL score was predicted using the 'Random Forest' method, based on visual acuity (VA) of better and worse eyes (better-eye and worse-eye VA) and total deviation (TD) values from the IVF. For comparison, VRQoL scores were regressed (linear regression) against: (i) mean of TD (IVF MD); (ii) better-eye VA; (iii) worse-eye VA; and (iv) IVF MD and better- and worse-eye VAs. The rank of importance of IVF test points was identified using the Random Forest method.The root mean of squared prediction error associated with the Random Forest method (0.30 to 1.97) was significantly smaller than those with linear regression models (0.34 to 3.38, p<0.05, ten-fold cross validation test). Worse-eye VA was the most important variable in all VRQoL tasks. In general, important VF test points were concentrated along the horizontal meridian. Particular areas of the IVF were important for different tasks: peripheral superior and inferior areas in the left hemifield for the 'letters and sentences' task, peripheral, mid-peripheral and para-central inferior regions for the 'walking' task, the peripheral superior region for the 'going out' task, and a broad scattered area across the IVF for the 'dining' task.The VRQoL prediction model with the Random Forest method enables clinicians to better understand patients' VRQoL based on standard clinical measurements of VA and VF.http://europepmc.org/articles/PMC3592814?pdf=render
spellingShingle Hiroshi Murata
Hiroyo Hirasawa
Yuka Aoyama
Kenji Sugisaki
Makoto Araie
Chihiro Mayama
Makoto Aihara
Ryo Asaoka
Identifying areas of the visual field important for quality of life in patients with glaucoma.
PLoS ONE
title Identifying areas of the visual field important for quality of life in patients with glaucoma.
title_full Identifying areas of the visual field important for quality of life in patients with glaucoma.
title_fullStr Identifying areas of the visual field important for quality of life in patients with glaucoma.
title_full_unstemmed Identifying areas of the visual field important for quality of life in patients with glaucoma.
title_short Identifying areas of the visual field important for quality of life in patients with glaucoma.
title_sort identifying areas of the visual field important for quality of life in patients with glaucoma
url http://europepmc.org/articles/PMC3592814?pdf=render
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