Predicting Risk of Motor Vehicle Collisions in Patients with Glaucoma: A Longitudinal Study.

To evaluate the ability of longitudinal Useful Field of View (UFOV) and simulated driving measurements to predict future occurrence of motor vehicle collision (MVC) in drivers with glaucoma.Prospective observational cohort study.117 drivers with glaucoma followed for an average of 2.1 ± 0.5 years.Al...

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Main Authors: Carolina P B Gracitelli, Andrew J Tatham, Erwin R Boer, Ricardo Y Abe, Alberto Diniz-Filho, Peter N Rosen, Felipe A Medeiros
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4591330?pdf=render
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author Carolina P B Gracitelli
Andrew J Tatham
Erwin R Boer
Ricardo Y Abe
Alberto Diniz-Filho
Peter N Rosen
Felipe A Medeiros
author_facet Carolina P B Gracitelli
Andrew J Tatham
Erwin R Boer
Ricardo Y Abe
Alberto Diniz-Filho
Peter N Rosen
Felipe A Medeiros
author_sort Carolina P B Gracitelli
collection DOAJ
description To evaluate the ability of longitudinal Useful Field of View (UFOV) and simulated driving measurements to predict future occurrence of motor vehicle collision (MVC) in drivers with glaucoma.Prospective observational cohort study.117 drivers with glaucoma followed for an average of 2.1 ± 0.5 years.All subjects had standard automated perimetry (SAP), UFOV, driving simulator, and cognitive assessment obtained at baseline and every 6 months during follow-up. The driving simulator evaluated reaction times to high and low contrast peripheral divided attention stimuli presented while negotiating a winding country road, with central driving task performance assessed as "curve coherence". Drivers with MVC during follow-up were identified from Department of Motor Vehicle records.Survival models were used to evaluate the ability of driving simulator and UFOV to predict MVC over time, adjusting for potential confounding factors.Mean age at baseline was 64.5 ± 12.6 years. 11 of 117 (9.4%) drivers had a MVC during follow-up. In the multivariable models, low contrast reaction time was significantly predictive of MVC, with a hazard ratio (HR) of 2.19 per 1 SD slower reaction time (95% CI, 1.30 to 3.69; P = 0.003). UFOV divided attention was also significantly predictive of MVC with a HR of 1.98 per 1 SD worse (95% CI, 1.10 to 3.57; P = 0.022). Global SAP visual field indices in the better or worse eye were not predictive of MVC. The longitudinal model including driving simulator performance was a better predictor of MVC compared to UFOV (R2 = 0.41 vs R2 = 0.18).Longitudinal divided attention metrics on the UFOV test and during simulated driving were significantly predictive of risk of MVC in glaucoma patients. These findings may help improve the understanding of factors associated with driving impairment related to glaucoma.
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spelling doaj.art-5dc09d2e5b414278b5176100c2a6fa362022-12-21T17:26:23ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-011010e013828810.1371/journal.pone.0138288Predicting Risk of Motor Vehicle Collisions in Patients with Glaucoma: A Longitudinal Study.Carolina P B GracitelliAndrew J TathamErwin R BoerRicardo Y AbeAlberto Diniz-FilhoPeter N RosenFelipe A MedeirosTo evaluate the ability of longitudinal Useful Field of View (UFOV) and simulated driving measurements to predict future occurrence of motor vehicle collision (MVC) in drivers with glaucoma.Prospective observational cohort study.117 drivers with glaucoma followed for an average of 2.1 ± 0.5 years.All subjects had standard automated perimetry (SAP), UFOV, driving simulator, and cognitive assessment obtained at baseline and every 6 months during follow-up. The driving simulator evaluated reaction times to high and low contrast peripheral divided attention stimuli presented while negotiating a winding country road, with central driving task performance assessed as "curve coherence". Drivers with MVC during follow-up were identified from Department of Motor Vehicle records.Survival models were used to evaluate the ability of driving simulator and UFOV to predict MVC over time, adjusting for potential confounding factors.Mean age at baseline was 64.5 ± 12.6 years. 11 of 117 (9.4%) drivers had a MVC during follow-up. In the multivariable models, low contrast reaction time was significantly predictive of MVC, with a hazard ratio (HR) of 2.19 per 1 SD slower reaction time (95% CI, 1.30 to 3.69; P = 0.003). UFOV divided attention was also significantly predictive of MVC with a HR of 1.98 per 1 SD worse (95% CI, 1.10 to 3.57; P = 0.022). Global SAP visual field indices in the better or worse eye were not predictive of MVC. The longitudinal model including driving simulator performance was a better predictor of MVC compared to UFOV (R2 = 0.41 vs R2 = 0.18).Longitudinal divided attention metrics on the UFOV test and during simulated driving were significantly predictive of risk of MVC in glaucoma patients. These findings may help improve the understanding of factors associated with driving impairment related to glaucoma.http://europepmc.org/articles/PMC4591330?pdf=render
spellingShingle Carolina P B Gracitelli
Andrew J Tatham
Erwin R Boer
Ricardo Y Abe
Alberto Diniz-Filho
Peter N Rosen
Felipe A Medeiros
Predicting Risk of Motor Vehicle Collisions in Patients with Glaucoma: A Longitudinal Study.
PLoS ONE
title Predicting Risk of Motor Vehicle Collisions in Patients with Glaucoma: A Longitudinal Study.
title_full Predicting Risk of Motor Vehicle Collisions in Patients with Glaucoma: A Longitudinal Study.
title_fullStr Predicting Risk of Motor Vehicle Collisions in Patients with Glaucoma: A Longitudinal Study.
title_full_unstemmed Predicting Risk of Motor Vehicle Collisions in Patients with Glaucoma: A Longitudinal Study.
title_short Predicting Risk of Motor Vehicle Collisions in Patients with Glaucoma: A Longitudinal Study.
title_sort predicting risk of motor vehicle collisions in patients with glaucoma a longitudinal study
url http://europepmc.org/articles/PMC4591330?pdf=render
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