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Editors Selection IGR 12-1

Clinical Examination Methods: RNFL and Psychophysical performance

Pradeep Ramulu

Comment by Pradeep Ramulu on:

58843 Glaucomatous retinal nerve fiber layer thickness loss is associated with slower reaction times under a divided attention task, Tatham AJ; Boer ER; Rosen PN et al., American Journal of Ophthalmology, 2014; 158: 1008-1017.e2


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Prior work has demonstrated that drivers with glaucoma demonstrate driving difficulties and are more likely to be at fault for a motor vehicle accident. A general assumption, supported by some evidence, is that these driving problems were primarily the result of vision loss, i.e., the inability to observe threats presenting in their peripheral vision.

In the current cross-sectional study, Tatham and colleagues observe that a specific driving simulator metric (reaction time to a peripheral stimulus) was worse with greater retinal nerve fiber loss as defined by SD-OCT. Reaction time was measured during a divided attention task in which patients were asked to negotiate a series of curves while maintaining lane position or follow a car moving at varying speed at a fixed distance. Performance of both central tasks was similar amongst patients with and without glaucoma, while reaction time to peripheral stimuli was slower amongst glaucoma patients, and was noted to be progressively slower with lower rNFL thickness. Of note, slower reaction times were only found when low contrast peripheral stimuli, likely near the threshold of perceptibility, were presented and were not observed for medium or high contrast stimuli.

The authors' findings raise an interesting question: Why would rNFL thickness predict reaction time independent of VF loss severity? One possibility is that rNFL thickness predicts visual abilities (i.e., motion detection) not evaluated in SAP. Alternately, a growing literature suggests that rNFL thickness may be lower in Alzheimer's dementia and early stages of cognitive loss, in which case the observed findings may reflect the ability of OCT to predict cognitive ability. Further research is needed to distinguish these possibilities, and to establish the extent to which OCT may be used to predict functional outcomes independent of standard visual metrics.



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