June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Visual field loss and fitness to drive: preliminary results
Author Affiliations & Notes
  • julien Adrian
    Streetlab, Paris, France
  • Caroline de Montleau
    Streetlab, Paris, France
  • Jose Alain Sahel
    UPMC, Pittsburgh, Pennsylvania, United States
    Institut de la vision, Paris, Île-de-France, France
  • Gérard Saillant
    FIA, Paris, France
  • Philippe Chaumet-Riffaud
    Centre Hospitalier National d'Ophtalmologie des Quinze-Vingts, Paris, Île-de-France, France
  • Footnotes
    Commercial Relationships   julien Adrian Streetlab, Code P (Patent); Caroline de Montleau None; Jose Sahel Pixium Vision, Code I (Personal Financial Interest), GenSight Biologics, Code P (Patent); Gérard Saillant None; Philippe Chaumet-Riffaud None
  • Footnotes
    Support  none
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 2467 – F0044. doi:
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      julien Adrian, Caroline de Montleau, Jose Alain Sahel, Gérard Saillant, Philippe Chaumet-Riffaud; Visual field loss and fitness to drive: preliminary results. Invest. Ophthalmol. Vis. Sci. 2022;63(7):2467 – F0044.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Drivers with visual field loss (VFL) such as glaucoma have higher risk of motor vehicle accidents and poorer driving performance when compared to age-matched drivers with no visual field loss. To date, conventional visual field tests have strong limitations in predicting on-road driving performance of VFL drivers. We developed a new screening-test (Driving Visual Field Attentional Test) for drivers with peripheral VFL such as individuals with glaucoma.
The aim of this study was to assess whether or not the Driving Visual Field Attentional Test is able to predict the outcome of an on-road driving test in drivers with VFL.

Methods : Twelve drivers with binocular VFL, aged 65.2 ±9.7, and twenty-four control drivers (matched for age and sex) aged 61.3±11,5, all holders of a driving license and active drivers, were recruited. They were asked to fill in a questionnaire about medical history, driving habits and motor vehicle collisions. They subsequently underwent an ophthalmologic examination including a battery of perimetric tests: Goldmann II-4 and III-1 and Esterman. Finally, they completed the Driving Visual Field Attentional Test, a UFOV test, a MMSE, and performed a practical on-road test under the supervision of expert evaluators. Driving evaluators were not aware of drivers’ visual status. The receiver operating characteristic (ROC) curve was used to investigate the ability of the different tests to discriminate between safe and unsafe drivers.

Results : Drivers with VFL detected fewer peripheral targets (p=.002) compared to the control drivers group. Four drivers with VFL failed the driving test. Three drivers with VFL and five controls were found to be “questionable”. ROC analysis revealed that the Driving Visual Field Attentional Test was an excellent predictor of failing the road test with an area-under-the-curve (AUC) value of 0.86 (CI: 0.58-1.0, p=0.01). UFOV also reached acceptable predictive power (AUC= 0.72, CI: 0.49-0.95, p=0.06). A cut-off score set at 28 non-responses provided 75% sensitivity (i.e., 75% of people who failed the road test were correctly identified) with a 100% specificity.

Conclusions : Preliminary analyses indicate that Driving Visual Field Attentional Test is a reliable predictor of at-risk driving for patients with visual field loss. Further testing with more subjects will be done to confirm these preliminary results.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

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