Related Experiment Video
Updated: Jun 22, 2026

Using Retinal Imaging to Study Dementia
Published on: November 6, 2017
Variability in depressive symptoms predicts cognitive decline in age-related macular degeneration
Barry W Rovner1, Robin J Casten, Benjamin E Leiby
1Department of Psychiatry and Neurology, Jefferson Medical College, Philadelphia, PA 19107, USA. barry.rovner@jefferson.edu
Objective:
The measurement of affective symptoms in older persons who decline cognitively is uncertain. The authors investigated whether mood variability predicts dementia in patients with age-related macular degeneration (AMD).
Design:
Three-year observational study after a clinical trial.
Setting:
Community follow-up of outpatients ascertained from retina clinics.
Participants:
One hundred sixty patients with AMD.
Measurements:
Geriatric Depression Scale (GDS) administered every 2 weeks for 6 months to subjects; Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) administered to subjects' knowledgeable informants.
Results:
Twenty-three subjects (14.4%) declined cognitively. Age, education, baseline GDS score > or =5, and variability in GDS scores (i.e., fluctuations between adjacent time points) were associated with cognitive decline. For GDS variability, each 1 unit increase in the residual standard deviation (SD) of the GDS increased the risk for cognitive decline by 93% (IDR = 1.92; 95% CI [1.27-2.91]). Thus, subjects with a residual SD of 1 were nearly twice as likely to become demented as subjects with no variability in GDS scores. The risk for subjects with SDs of 2 increased more than threefold (IDR = 3.68; 95% CI [1.61-8.47]). A multiple regression analysis showed that GDS variability was a significant risk factor for dementia after controlling for significant covariates.
Conclusion:
These data suggest a useful approach to conceptualizing and measuring depressive symptoms in older persons. Variability in self-reported mood may be an early sign of dementia and may offer new insights into the neurobiological mechanisms linking depression and cognition
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