Purchase this article with an account.
Deanna J. Taylor, Nicholas D. Smith, David P. Crabb; Searching for Objects in Everyday Scenes: Measuring Performance in People With Dry Age-Related Macular Degeneration. Invest. Ophthalmol. Vis. Sci. 2017;58(3):1887-1892. doi: 10.1167/iovs.16-21122.
Download citation file:
© 2017 Association for Research in Vision and Ophthalmology.
Treatment success in clinical trials for AMD would ideally be aligned to measurable performance in visual tasks rather than imperceptible changes on clinical charts. We test the hypothesis that patients with dry AMD perform worse than visually healthy peers on computer-based surrogates of “real-world” visual search tasks.
A prospective case-control study was conducted in which patients with dry AMD performed a computer-based “real-world” visual search task. Participants searched for targets within images of everyday scenes while eye movements were recorded. Average search times across the images were recorded as a primary outcome measure. Comparisons were made against a 90% normative limit established in peers with healthy vision (controls). Eye movement parameters were examined as a secondary outcome measure.
Thirty-one patients and 33 controls with median (interquartile range) age of 75 (70–79) and 71 (66–75) years and logMAR binocular visual acuity 0.2 (0.18–0.31) and −0.06 (−0.12 to 0), respectively, were examined. Four, 18, and 9 patients were categorized as having early, intermediate, and late AMD, respectively. Nineteen (61%) patients exceeded the 90% normative limits for average search time; this was statistically significant (Fisher's exact test, P < 0.0001). On average, patients made smaller saccades than controls (P < 0.001).
People with dry AMD, certainly those with advanced disease, are likely to have measurable difficulties beyond those observed in visually healthy peers on “real-world” search tasks. Further work might establish this type of task as a useful outcome measure for clinical trials.
This PDF is available to Subscribers Only