September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Searching for objects in everyday scenes and recognising faces: measuring performance in people with dry age-related macular degeneration (AMD)
Author Affiliations & Notes
  • Deanna J Taylor
    Optometry and Visual Sciences, City University London, London, United Kingdom
  • Nicholas Smith
    Optometry and Visual Sciences, City University London, London, United Kingdom
  • Alison Binns
    Optometry and Visual Sciences, City University London, London, United Kingdom
  • David Crabb
    Optometry and Visual Sciences, City University London, London, United Kingdom
  • Footnotes
    Commercial Relationships   Deanna Taylor, None; Nicholas Smith, None; Alison Binns, None; David Crabb, Allergan PLC (R)
  • Footnotes
    Support  Unrestricted Independent Investigator Award from Roche
Investigative Ophthalmology & Visual Science September 2016, Vol.57, No Pagination Specified. doi:
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      Deanna J Taylor, Nicholas Smith, Alison Binns, David Crabb; Searching for objects in everyday scenes and recognising faces: measuring performance in people with dry age-related macular degeneration (AMD). Invest. Ophthalmol. Vis. Sci. 201657(12):.

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

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Abstract

Purpose : Treatment success in a clinical trial for age-related macular degeneration (AMD) would ideally be aligned to measureable performance in visual tasks rather than imperceptible changes on a clinical chart. We sought to test the hypothesis that patients with dry AMD perform worse than visually healthy peers on computer-based surrogates of ‘real world’ tasks in a prospective case-control study.

Methods : People (>60 years, logMAR binocular visual acuity (BVA) 0.7 or better) categorised with varying severity of dry AMD performed two previously validated computer-based ‘real world’ visual tasks. In a search task, participants were instructed to find items within digital photographs of everyday indoor and outdoor scenes (Smith et al 2011). Average search times across the images were recorded for each participant. In a face recognition (FR) task participants completed a modified version of the Cambridge Face Memory Test (Glen et al 2012). Percentage of correctly identified faces was used as an outcome measure for performance for each participant. Comparisons for both tasks were made against a 90% normative limit for the outcome measures established in 33 age-related people with healthy vision (median [interquartile range; IQR] age 71 [66 to 75] years, BVA -0.06 [-0.12 to 0]) who performed the same tests.

Results : Sixteen patients (median [IQR] age 76 [74 to 78] years, BVA 0.2 [0.18 to 0.4]) from a recruitment target of 30 were examined. Two, ten and four patients were categorised as having early, intermediate and late AMD respectively (Ferris et al 2013). Eight (50%) patients exceeded the 90% normative limits for delayed average search time and this number was statistically significant (Fisher’s Exact Test, p= 0.0026). Three patients (19%) recorded a FR performance worse than the 90% limit (p=0.38); two of these had geographic atrophy (late AMD).

Conclusions : People with dry AMD, certainly those with more advanced disease (geographic atrophy), are likely to have measurable difficulties beyond those observed in visually healthy peers on search and face recognition tasks as presented on a computer set-up. Further work might establish results from these types of tasks to be useful in patient management and as end-points for clinical trials for new treatments for dry AMD.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

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