Association of Hypoglycemic Treatment Regimens With Cardiovascular Outcomes in Overweight and Obese Subjects With Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To assess the association of hypoglycemic treatment regimens with cardiovascular adverse events and mortality in a large population of type 2 diabetic patients at increased cardiovascular risk. RESEARCH DESIGN AND METHODS: This analysis included 8,192 overweight patients with type 2 diabetes from the Sibutramine Cardiovascular Outcomes (SCOUT) trial randomized to lifestyle intervention with or without sibutramine for up to 6 years. Patients were grouped according to hypoglycemic treatment at baseline. The primary end point was the time from randomization to the first occurrence of a primary outcome event (POE), nonfatal myocardial infarction, nonfatal stroke, resuscitation after cardiac arrest, or cardiovascular death. Multivariable Cox proportional hazards regression models were used to assess the impact of antiglycemic treatment on POE and all-cause mortality. RESULTS: Treatments for type 2 diabetes were as follows: diet alone (n = 1,394 subjects), metformin monotherapy (n = 1,631), insulin monotherapy (n = 1,116), sulfonylurea monotherapy (n = 1,083), metformin plus sulfonylurea (n = 1,565), and metformin plus insulin (n = 1,000); 905 subjects experienced a POE and 708 died. Metformin monotherapy was associated with lower risk of POE than insulin (hazard ratio [HR], 0.74; 95% CI, 0.57-0.95; P = 0.02). Diet alone also was associated with lower risk of POE (HR, 0.65; 95% CI, 0.48-0.87; P = 0.004). Metformin monotherapy also was associated with lower mortality (HR, 0.73; 95% CI, 0.54-0.99; P < 0.05), whereas no other monotherapies or combination therapies were significantly associated with POE or all-cause mortality compared with insulin as monotherapy. CONCLUSIONS: In obese patients with type 2 diabetes and high risk of cardiovascular disease, monotherapy with metformin or diet-only treatment was associated with lower risk of cardiovascular events than treatment with insulin.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".