Effect of Cognitive Demand on Visual Field Performance in Senior Drivers with Glaucoma

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Effect of Cognitive Demand on Visual Field Performance in Senior Drivers with Glaucoma

Viswa Gangeddula, Maud Ranchet, Abiodun Akinwuntan, Kathryn Bollinger, Hannes Devos

To cite this version:

Viswa Gangeddula, Maud Ranchet, Abiodun Akinwuntan, Kathryn Bollinger, Hannes Devos. Effect of Cognitive Demand on Visual Field Performance in Senior Drivers with Glaucoma. American Congress of Rehabilitation Medicine, Oct 2017, Atlanta, GA, United States. �hal-01721071�

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Background

ØGlaucoma leads to peripheral

visual field loss.

ØVisual field loss may affect safe

driving.

ØSafe driving is determined by

intact visual field, cognitive

capacity, and cognitive demand.

ØThe relationship between cognitive

demand and visual field in drivers with glaucoma is unclear.

Purpose

Results

Ø No significant differences between the glaucoma and healthy control groups in demographics and clinical measures.

Ø Glaucoma group performed worse on mean deviation both eyes and standard pattern deviation right eye from Humphrey Visual Field Analyzer.

Methods

Discussion

Acknowledgement

References

ØIncrease in cognitive demand

reduced the functional visual field performance in both groups.

ØHowever, drivers with glaucoma

performed worse on the visual field task, especially when

dynamic visual flow was added.

ØDriving assessments should

consider the participants’

physiological visual field, their cognitive capacity, and the

cognitive demand of the task to

fully appreciate the impact of any visual field loss performance.

Ø This study was funded in part by

the Fight for Sight / Prevent

Blindness America Public Health Award and a pilot grant by the

Culver Vision Discovery Institute.

Ø The authors acknowledge the

contributions of Dr. Sumner

Fishbein, and Dr. Lane Ulrich.

Ø To compare the effect of cognitive

demand on functional visual field between drivers with glaucoma

and control drivers.

Effect of Cognitive Demand on Functional Visual Field Performance in Senior Drivers with Glaucoma

Viswa Gangeddula, MS1_{, Maud Ranchet, PhD}2_{, Abiodun E Akinwuntan, PhD, MPH, MBA}1_{, Kathryn Bollinger, MD}3_{, Hannes Devos, PhD}1

1_{Laboratory for Advanced Rehabilitation Research in Simulation (LARRS), Department of Physical Therapy and Rehabilitation Science,}

University of Kansas Medical Center, Kansas City, KS, USA, 2_{Univ Lyon, IFSTTAR, Lyon, France,}3_{Department of Ophthalmology, Medical College of Georgia, Augusta}

University, Augusta, Georgia, USA

[email protected] http://larrs.kumc.edu

1. Ball KK, Roenker DL, Bruni JR. Developmental

changes in attention and visual search throughout adulthood. Advances in psychology (1990) 69:489-508.

2. Gangeddula, V., et al., Effect of Cognitive Demand on

Functional Visual Field Performance in Senior Drivers with Glaucoma. Frontiers in Aging Neuroscience,

2017. 9(286). Methods

Ø 20 drivers with open-angle

glaucoma and 13 age- and sex-matched controls.

Ø Visual field performance was

evaluated under different

conditions of cognitive demand using an interactive, desktop

driving simulator (Figures 1 & 2).

Ø Primary outcomes: Number of

correct responses and response time on visual field.

Figure 3. Comparison of correct responses in static (condition 1), dynamic (condition 2), and active driving (condition 3).

Figure 4. Comparison of response time static (condition 1), dynamic (condition 2), and active driving (condition 3).

Ø Significant decrease in correct response time and response time with increased cognitive demand (Wilcoxon Signed Rank, p < 0.05).

Ø Glaucoma group responded less accurately and slower in the dynamic visual field task without active driving (condition 2) and with active driving (condition 3)

compared with healthy controls (p < 0.05) (Figures 3 and 4).

Ø Increase in complexity disproportionally affected visual field in glaucoma (Wilcoxon rank sum, p < 0.05). 109.00 110.00 111.00 112.00 113.00 114.00

Condition 1 Condition 2 Condition 3

N um be r of co rr ect r esp on se s Glaucoma^ Controls^ P = 0.01 P = 0.01 0.00 0.20 0.40 0.60 0.80 1.00

Condition 1 Condition 2 Condition 3

R esp on se ti m e (se cs) Glaucoma^ Controls^ P = 0.01 P = 0.04

Figure 2: Driving simulator A: Static visual field task B : Dynamic visual field task C: Dynamic visual field task

with active driving

Figure 1: Three different visual field conditions used in the study. Red target symbol was to be detected while focusing on a (A) central white target; (B) white lead car driving at 45 mph (no driving); (C) white lead car while driver maintains 45 mph.

^ indicate median values; Wilcoxon rank sum test