Short report: suboptimal diabetes care in high‐risk diabetic patients attending a specialist retina clinic
Bibliographic record
Abstract
AIMS: Individuals with diabetic retinopathy (DR) represent a high-risk group who would benefit from intensive metabolic control and risk factor management. This brief report examines quality of care among diabetic patients attending a tertiary retinal clinic. METHODS: A cross-sectional survey, notes review, and slit-lamp examination was conducted in 139 diabetic patients attending a specialist retinal clinic to assess the quality of comprehensive diabetes care. DR was graded according to the Early Treatment Diabetic Retinopathy Study scale. RESULTS: The prevalence of non-proliferative DR (NPDR) and proliferative DR (PDR) was 39.6 and 35.2%, respectively. The prevalence of microalbuminuria in patients with no DR, NPDR and PDR was 32, 54.1 and 68.8%, respectively. Glycaemic control was suboptimal (mean HbA(1c) 8.0 +/- 1.8%) and 15.8% were current smokers. Drugs affecting the renin-angiotensin system were used by only 61.9% of patients with both DR and microalbuminuria, and aspirin by only 35.3%. CONCLUSIONS: These data suggest that diabetes care in this high-risk population with established microvascular complications was suboptimal. Specialist clinics dealing with diabetic complications may be a setting where quality improvement strategies to reduce morbidity and mortality should be focused.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".