The relationship between retinal hemodynamics and systemic markers of endothelial function and inflammation in type 2 diabetes
Bibliographic record
Abstract
Abstract Purpose The aim of the study was to investigate the associations, if any, between retinal hemodynamics and systemic markers of endothelial function and inflammation in patients with type 2 diabetes and non‐proliferative diabetic retinopathy (NPDR). Methods Retinal blood flow measurements and blood serum samples were obtained from 9 healthy controls (Group 1, mean age 53.8 yrs, SD 11.7), 23 patients with mild‐to‐moderate NPDR (Group 2, mean age 61.4 yrs, SD 8.5; duration 9.9 yrs, SD 8.8) and 14 patients with moderate‐to‐severe NPDR (Group 3, mean age 60.3 yrs, SD 9.9; duration 17.0 yrs, SD 9.4). Retinal blood flow was measured in the supero‐temporal arteriole using the Canon Laser Blood Flowmeter. Blood samples were collected to derive levels of intercellular adhesion molecule (ICAM‐1), vascular adhesion molecule (VCAM‐1), E‐selectin and von Willebrand factor (vWF). Results Diameter, velocity, maximum‐to‐minimum velocity ratio and flow were the same across the groups and did not change over a 6 month follow‐up. A1c and ICAM‐1 were significantly elevated across the groups (p=0.001 and p=0.030, resp., ANOVA). VCAM‐1 (r =0.325, p=0.046) and vWF (r =0.334, p=0.050) showed relatively weak associations with baseline max:min velocity ratio. vWF showed moderate associations with change in velocity (r = 0.571, p=0.007) and change blood flow (r = 0.455, p=0.038). Conclusion The relationship between endothelial dysfunction and inflammation markers and retinal hemodynamics in type 2 diabetes is complex since not all markers show an association. This work is on‐going.
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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".