Macular vessel density is associated with cognitive function in preclinical p.R544C NOTCH3 mutation carriers
Bibliographic record
Abstract
BACKGROUND: The study aimed to examine the relationship between retinal microcirculation, brain white matter hyperintensities (WMH) seen on magnetic resonance imaging (MRI), and cognitive decline in asymptomatic carriers of NOTCH3 mutations, a preclinical stage of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. METHODS: Forty-nine asymptomatic carriers without stroke history or cognitive complaints were studied. Retinal vessel density and WMH volume were measured via optical coherence tomography angiography and MRI, respectively. Cognitive function was assessed using various tests. RESULTS: In a multivariable regression model which included both, the whole brain WMH volume and parafoveal vessel density of superficial retinal plexus (SRP) as independent variables, parafoveal vessel density of SRP emerged as a significant predictor for Montreal Cognitive Assessment (MoCA) score ( β = -0.31; 95% confidence interval, -0.1516 to -0.0002; p = 0.044) in this cohort, and consistent findings were observed for Color Trails Tests (CTT)-1 and CTT-2 scores. CONCLUSION: In asymptomatic NOTCH3 mutation carriers, higher parafoveal vessel density of the SRP may serve as an indicator of cognitive decline, and may also indicate autoregulatory compensatory mechanisms in response to a dysfunctional capillary plexus, potentially signifying early-stage cognitive decline.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".