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Predicting visual acuity from visual field sensitivity in age-related macular degeneration

Yes / Purpose: To investigate how well visual field sensitivity predicts visual acuity at the same locations in macular disease, and to assess whether such predictions may be useful for selecting an optimum area for fixation training.

Methods: Visual field sensitivity and acuity were measured at nine locations in the central 10° in 20 people with AMD and stable foveal fixation. A linear mixed model was constructed to predict acuity from sensitivity, taking into account within-subject effects and eccentricity. Cross validation was used to test the ability to predict acuity from sensitivity in a new patient. Simulations tested whether sensitivity can predict nonfoveal regions with greatest acuity in individual patients.

Results: Visual field sensitivity (P < 0.0001), eccentricity (P = 0.007), and random effects of subject on eccentricity (P = 0.043) improved the model. For known subjects, 95% of acuity prediction errors (predicted − measured acuity) fell within −0.21 logMAR to +0.18 logMAR (median +0.00 logMAR). For unknown subjects, cross validation gave 95% of acuity prediction errors within −0.35 logMAR to +0.31 logMAR (median −0.01 logMAR). In simulations, the nonfoveal location with greatest predicted acuity had greatest “true” acuity on median 26% of occasions, and median difference in acuity between the location with greatest predicted acuity and the best possible location was +0.14 logMAR (range +0.04 to +0.17).

Conclusions: The relationship between sensitivity and acuity in macular disease is not strongly predictive. The location with greatest sensitivity on microperimetry is unlikely to represent the location with the best visual acuity, even if eccentricity is taken into account. / College of Optometrists Postdoctoral Research Award (JD and ATA; London, UK) and National Institute for Health Research (NIHR) Postdoctoral Fellowship (ATA; London, UK). Presents independent research funded by the NIHR. / Research Development Fund Publication Prize Award winner, August 2018.

Identiferoai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/16638
Date January 2018
CreatorsDenniss, Jonathan, Baggaley, H.C., Astle, A.T.
Source SetsBradford Scholars
LanguageEnglish
Detected LanguageEnglish
TypeArticle, Published version
RightsCopyright 2018 The Authors. This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/)., CC-BY

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