Retinal vessel density correlates with cognitive function in older adults
Bibliographic record
Abstract
Abstract Background Accumulating evidence indicates that microvascular alterations in the brain, especially at the capillary level, are one of the major contributors to cognitive impairment and dementia in older adults. The brain and retinal microvasculature share similar anatomic and physiologic features. Alterations of retinal microvasculature reflect similar changes in brain. We examined the associations between retinal microvascular density, cognition and physical fitness in healthy older adults with no reported cognitive decline. Method Twenty cognitively normal older adults (age: 70.3 ± 4.6 years) were recruited. Both eyes of each subject were imaged using optical coherence tomography angiography. The vessel density of the retinal vascular network (RVN), superficial vascular plexus (SVP), and deep vascular plexus (DVP) was measured. Cognitive function was tested using the Mini‐mental state examination (MMSE) and Montreal Cognitive Assessment (MoCA), while physical performance was evaluated using the YMCA cycle ergometer test. Partial correlations (r partial ) were computed between measures of retinal microvascular density, cognitive function, and physical performance. Result The MoCA was significantly correlated to vessel density of RVN (r partial = 0.54, P = 0.002) and SVP (r partial = 0.59, P < 0.001), but not DVP (r partial = ‐0.01, P = 0.99). MoCA also showed a trend toward correlation with YMCA total work (TW‐YMCA, r partial = 0.28, P = 0.14). Retinal microvascular density was not related to TW‐YMCA (r partial = ‐ 0.23 ∼ 0.12, P > 0.05). Conclusion The MoCA was significantly correlated to vessel density of RVN (r partial = 0.54, P = 0.002) and SVP (r partial = 0.59, P < 0.001), but not DVP (r partial = ‐0.01, P = 0.99). MoCA also showed a trend toward correlation with YMCA total work (TW‐YMCA, r partial = 0.28, P = 0.14). Retinal microvascular density was not related to TW‐YMCA (r partial = ‐ 0.23 ∼ 0.12, P > 0.05).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".