Retinal Hemodynamics in Early Diabetic Macular Edema
Bibliographic record
Abstract
The objective of this study was to establish the baseline retinal hemodynamic characteristics of stratified groups of diabetic patients at increasing risk for the development of diabetic macular edema (DME). Group 1 had 50 control subjects, group 2 had 56 diabetic patients without clinically visible retinopathy, group 3 had 54 diabetic patients with microaneurysms and/or hard exudates within two disc diameters of the fovea in the absence of clinically manifest DME, and group 4 had 40 patients with clinically manifest DME. Retinal hemodynamics (diameter, velocity, maximum-to-minimum velocity ratio, and flow) were assessed. Intraocular pressure, blood pressure, and relevant systemic markers of diabetes control and complications were also undertaken. The maximum-to-minimum velocity ratio was elevated with increasing risk of clinically significant DME (P < 0.0001). No significant differences were found between the groups with respect to diameter, velocity, or flow. The maximum-to-minimum velocity ratio was correlated to age, duration of diabetes, blood pressure, pulse rate, intraocular pressure, and serum potassium levels. In conclusion, the maximum-to-minimum velocity ratio was significantly increased with increasing risk of development of DME. Retinal arteriolar hemodynamics were positively correlated to age, duration of diabetes, and blood pressure. These findings suggest a reduction in the compliance (i.e., an increase of vascular rigidity) of the arteriolar circulation with increasing risk of DME.
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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) | 0.001 | 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".