Retinal Vessel Traits and Age‐Related Eye Disease in the Canadian Longitudinal Study on Aging
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: To cross-sectionally and longitudinally examine whether retinal vessel traits are associated with glaucoma-related outcomes (glaucoma, cup-to-disc ratio [CDR] and intraocular pressure [IOP]) and age-related macular degeneration (AMD). METHODS: Baseline and 3-year follow-up data from the 30 097 participants of the Canadian Longitudinal Study on Aging were used. The follow-up rate was 92%. QUARTZ, a deep learning algorithm, was used to extract data from retinal images including arteriolar and venular diameter, tortuosity and vertical CDR. Glaucoma and AMD were self-reported. IOP was measured. Multiple linear and logistic regression were used to adjust for demographic, lifestyle and clinical factors. RESULTS: Having wider arterioles was associated with a lower odds of glaucoma (OR = 0.36, 95% CI: 0.20, 0.65) at baseline but there was no association using longitudinal data. Instead, glaucoma at baseline was strongly associated with 3-year change in arteriolar diameter (β = -0.21, 95% CI: -0.37, -0.05) indicating that the cross-sectional association may have been due to reverse causality. Using longitudinal data, greater venular tortuosity was associated with a reduced 3-year development of glaucoma (OR = 0.52, 95% CI: 0.31, 0.87) and a 3-year reduction in the CDR (β = -0.006, 95% CI: -0.010, -0.002). Wider venular diameter was associated with a higher odds of AMD at baseline (OR = 2.77, 95% CI: 1.50, 5.15) and a higher odds of the 3-year development of AMD (OR = 4.15, 95% CI: 1.95, 8.82). CONCLUSIONS: Understanding the temporal relationship of changes in the retinal microvasculature and the development of eye disease may lead to better treatment and prevention strategies.
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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 | 0.001 | 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 it