The association between retinal vascular fractal dimension and cognitive function in the community-dwelling older adults cohort TIGER
Bibliographic record
Abstract
The small retinal vessels reflect cerebral microcirculation and its fractal dimension (Df), representing the complexity of the retinal microcirculation. However, the connection between retinal circulation and cognitive function lacked consistent and longitudinal evidence. This study aimed to explore the association between retinal vascular complexity and cognitive impairment over time in non-demented community-dwelling older adults. This four-year prospective cohort study (2015–2019) is part of the ongoing Taiwan Initiative for Geriatric Epidemiological Research (TIGER, 2011 to present). Of the 434 older adults (age >65) recruited, 207 participants were included for analysis. The retinal vascular Df was assessed by baseline images from fundus photography (2015–2017). Global (Montreal Cognitive Assessment-Taiwanese version, MoCA-T) and domain-specific cognition were assessed at the baseline and 2-year follow-up (2017–2019). The multivariable linear regression models and generalized linear mixed models were used to evaluate the association of Df with cognitive decline/impairment over time. Decreased left retinal vascular complexity was associated with poor attention performance (β = −0.40). As follow-up time increased, decreased vascular complexity was associated with poor memory performance (right: β = −0.25; left: β = −0.19), and decreased right vascular complexity was associated with poor attention performance (β = −0.18). Low retinal vascular complexity of the right or left eye may be differentially associated with cognitive domains in community-dwelling older adults over two years. The retinal vascular Df of either eye may be served as a screening tool for detecting cognitive impairment in the preclinical phase of dementia.
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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 | 0.015 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".