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Diabetic retinopathy and cognitive dysfunction: a systematic review and meta-analysis
1Evidence-Based Medicine Centre, School of Basic Medical Sciences, School of Nursing, Lanzhou University, Lanzhou, 730030, Gansu, China.
Acta Diabetologica
|February 3, 2022
Summary
Diabetic retinopathy (DR) significantly increases the risk of cognitive dysfunction, particularly affecting psychomotor and information processing speeds. This finding highlights DR as a potential indicator for identifying individuals at higher risk of cognitive decline.
Area of Science:
- Ophthalmology
- Neurology
- Endocrinology
Background:
- Diabetic retinopathy (DR) is a common complication of diabetes.
- Cognitive dysfunction is increasingly recognized as a comorbidity in diabetic patients.
- The relationship between DR and cognitive impairment requires further elucidation.
Purpose of the Study:
- To determine the association between diabetic retinopathy and cognitive dysfunction.
- To explore the impact of DR on specific cognitive domains.
- To synthesize existing evidence through meta-analysis.
Main Methods:
- Systematic literature search of multiple databases (PubMed, Embase, Web of Science, etc.) up to October 2021.
- Inclusion of 22 studies, with 15 contributing to the meta-analysis.
- Calculation of pooled odds ratios (ORs) and hazard ratios (HRs) with 95% confidence intervals (CIs).
Main Results:
- Diabetic retinopathy is associated with a significantly higher risk of cognitive dysfunction (OR = 2.45, HR = 1.34).
- The risk was consistent across cohort and cross-sectional studies and observed in Asia and Oceania, but not North America.
- A positive correlation exists between DR severity and cognitive impairment, primarily affecting psychomotor and information processing speeds. No association found in Type 1 Diabetes Mellitus (T1DM).
Conclusions:
- Diabetic retinopathy serves as a potential indicator for identifying individuals at high risk of cognitive dysfunction.
- Further research is needed to explore DR's impact on cognitive impairment across diverse demographics (age, gender, race) and populations.
- Understanding this relationship can inform early detection and intervention strategies.
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