Use of vascular risk‐modifying medications for diabetic patients differs between physician specialties
Bibliographic record
Abstract
AIMS: Although heart disease and stroke are the underlying causes of death in most people with diabetes, vascular risk modification targets are frequently not met. This study examined whether vascular risk-modifying medication utilization for diabetic patients differed among physician specialties. METHODS: A population-based study using administrative data from 105 715 people aged >/= 65 years with newly diagnosed diabetes in Ontario between 1994 and 2001. The receipt of antihypertensive and lipid-lowering drugs was compared between patients who had regular care from endocrinologists, internists/geriatricians and family physicians. Hierarchical logistic regression adjusted for patient-level differences, physician-level differences and patient clustering within physicians. RESULTS: Only two-thirds of patients received antihypertensive drugs and about one-quarter received lipid-lowering drugs. Compared with patients of family physicians, the adjusted odds ratios for antihypertensive drug use were 1.27 [95% confidence interval (CI) 1.16, 1.38] for patients of internists/geriatricians and 1.03 (95% CI 0.94, 1.12) for patients of endocrinologists. For lipid-lowering drugs, the odds ratios were 1.20 (95% CI 1.11, 1.30) for patients of internists/geriatricians and 1.58 (95% CI 1.42, 1.76) for patients of endocrinologists. CONCLUSIONS: Despite recommendations to use vascular risk-modifying medication for most older people with diabetes, many patients were not receiving these medications. Medication utilization differed between physician specialties, with family physicians having the lowest rates of use. Notably, although blood pressure control has the greatest evidence of benefit and is cost-saving, endocrinologists did not use antihypertensive drugs more often than family physicians after adjustment for other differences.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".