AWAREness of Diagnosis and Treatment of Chronic Kidney Disease in Adults With Type 2 Diabetes (AWARE-CKD in T2D)
Bibliographic record
Abstract
OBJECTIVES: Diabetes remains the leading contributor to the development of chronic kidney disease (CKD) and end-stage kidney disease, emphasizing the urgency of identifying barriers to early diagnosis and intervention. The primary objective of this study was to describe the awareness, values and preferences of physicians and patients with respect to managing CKD among patients with type 2 diabetes (T2D). METHODS: A cross-sectional survey was conducted among physicians and adult patients with T2D and CKD based on estimated glomerular filtration rate and urine albumin-to-creatinine ratio (uACR) measured within 1 year. Physicians were recruited from email networks across Canada, excluding Alberta, and patients were recruited from LMC Diabetes and Endocrinology clinics in Ontario and Quebec. Two separate surveys were developed by a steering committee. Survey responses from 160 physicians (60 general practitioners, 50 endocrinologists and 50 nephrologists) and 169 patients were analyzed descriptively. RESULTS: Gaps in physician care included insufficient use of uACR screening, limited knowledge or use of Kidney Disease Improving Global Outcomes (KDIGO) and KidneyWise resources and lower than expected prescription of recommended therapies. The patient data showed 51.5% of patients were unaware of a CKD diagnosis, and 75.6% of patients who received a prior CKD diagnosis would have preferred an earlier diagnosis. CONCLUSIONS: The results highlight several opportunities for improving CKD in T2D management. More education and clarity are needed for physicians interpreting uACR levels that should prompt a referral to a nephrologist, and additional understanding of kidney risk progression is vital for patients.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".