The Relationship Between Diabetic Retinopathy and Cognitive Impairment
Bibliographic record
Abstract
OBJECTIVE: Recent studies have shown an increased risk for cognitive impairment and dementia in patients with diabetes. An association between diabetic retinopathy (DR) and retinal microvasculature disease and cognitive impairment has been reported as potential evidence for a microvascular component to the cognitive impairment. It was hypothesized that severity of DR would be associated with cognitive impairment in individuals with type 2 diabetes. RESEARCH DESIGN AND METHODS: Three hundred eighty patients with type 2 diabetes were recruited from a population-based eye screening program and grouped by severity of DR as follows: no/mild DR (n=252) and proliferative diabetic retinopathy (PDR) (n=128). Each participant underwent psychosocial assessment; depression screening; ophthalmic and physical examination, including blood assays; and cognitive assessment with the Addenbrooke's Cognitive Examination-Revised (ACE-R), Mini-Mental State Examination (MMSE), and the Mini-Cog. General linear modeling was used to examine severity of DR and cognitive impairment, adjusting for confounders. RESULTS: Severity of DR demonstrated an inverse relationship with cognitive impairment (fully adjusted R2=0.415, P<0.001). Ethnicity contributed most to the variance observed (16%) followed by education (7.3%) and retinopathy status (6.8%). The no/mild DR group had lower cognitive impairment scores on ACE-R (adjusted mean±SE 77.0±1.9) compared with the PDR group (82.5±2.2, P<0.001). The MMSE cutoff scores showed that 12% of the no/mild DR group (n=31) had positive screening results for dementia or significant cognitive impairment compared with 5% in the PDR group (n=6). CONCLUSIONS: Patients with minimal DR demonstrated more cognitive impairment than those with advanced DR. Therefore, the increased prevalence of cognitive impairment in diabetes may be associated with factors other than evident retinal microvascular disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".