Evidence of suboptimal management of cardiovascular risk in patients with type 2 diabetes mellitus and symptomatic atherosclerosis
Bibliographic record
Abstract
BACKGROUND: Given that most deaths among patients with diabetes mellitus are due to cardiovascular disease, we sought to determine the extent to which medications proven to reduce cardiovascular mortality are prescribed for patients with type 2 diabetes who have symptomatic atherosclerosis (i.e., coronary artery disease [CAD], cerebrovascular disease [CBVD] or peripheral arterial disease [PAD]). METHODS: Administrative records from Saskatchewan Health were used to evaluate the use of antiplatelet agents, statins and angiotensin-converting enzyme (ACE) inhibitors by people with treated type 2 diabetes with and without symptomatic atherosclerosis. CAD and CBVD were defined by International Classification of Diseases (ninth revision) codes, and PAD was defined on the basis of pentoxifylline use or lower limb amputation. Multivariate logistic regression analysis was used to compare medication use in patients with and without PAD, with adjustments for differences in age, sex and comorbidity. RESULTS: In this cohort of 12,106 patients with type 2 diabetes (mean age 64 years, 55% male, mean follow-up 5 years), fewer than 25% received an antiplatelet agent or statin, and fewer than 50% received an ACE inhibitor. Although patients with CAD were more likely to receive antiplatelet agents, statins or ACE inhibitors than people without CAD (p < 0.001 for all), the overall use of these medications was suboptimal (37%, 29% and 60% respectively among patients with symptomatic CAD). Similar patterns of practice were found for patients with symptomatic CBVD and PAD. All 3 proven efficacious therapies were prescribed for only 11% of patients with CAD, 22% with CBVD and 12% with PAD. Patients with PAD who had undergone lower limb amputation were no more likely to subsequently receive antiplatelet agents or statins than those without an amputation. INTERPRETATION: Diabetic patients with symptomatic atherosclerotic disease are undertreated with medications known to reduce cardiovascular morbidity and mortality, perhaps because of a "glucocentric" view of diabetes. Programs to improve the quality of cardiovascular risk reduction in these high-risk patients are needed.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".