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Retinal thickness predicts the risk of cognitive decline over five years. | LitMetric

AI Article Synopsis

Article Abstract

Background: Dementia poses a significant burden on healthcare systems. Early identification of individuals at risk for cognitive decline is crucial. The retina, an extension of the central nervous system, reflects neurodegenerative changes. Optical coherence tomography (OCT) is a non-invasive tool for assessing retinal health and has shown promise in predicting cognitive decline. However, prior studies produced mixed results.

Methods: This study investigated a large cohort (n = 490) of Asian individuals attending memory clinics. Participants underwent comprehensive neuropsychological testing annually for five years. Retinal thickness was measured by OCT at baseline. We assessed the association between baseline retinal thickness and subsequent cognitive decline.

Results: Participants with a significantly thinner macular ganglion cell-inner plexiform layer (GCIPL) at baseline (≤ 79 μm) had a 38% greater risk of cognitive decline compared to those who did not (≥ 88 μm; p = 0.037). In a multivariable model accounting for age, education, cerebrovascular disease status, hypertension, hyperlipidemia, diabetes and smoking, thinner GCIPL was associated with an increased risk of cognitive decline (hazard ratio = 1.14, 95% CI = 1.01-1.30, p = 0.035). Retinal nerve fiber layer (RNFL) thickness was not associated with cognitive decline.

Conclusions: This study suggests that OCT-derived macular GCIPL thickness may be a valuable biomarker for identifying individuals at risk of cognitive decline. Our findings highlight GCIPL as a potentially more sensitive marker compared to RNFL thickness for detecting early neurodegenerative changes.

Trial Registration Number And Name Of The Trial Registry: National Healthcare Group Domain-Specific Review Board (NHG DSRB) reference numbers DSRB Ref: 2018/01368. Name of the trial: Harmonisation project.

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Source
http://dx.doi.org/10.1186/s13195-024-01627-0DOI Listing

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