Favorable Effects of Insulin Sensitizers Pertinent to Peripheral Arterial Disease in Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: The aim of this manuscript was to report the risk of incident peripheral arterial disease (PAD) in a large randomized clinical trial that enrolled participants with stable coronary artery disease and type 2 diabetes and compare the risk between assigned treatment arms. RESEARCH DESIGN AND METHODS: The Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) trial randomly assigned participants to insulin sensitization (IS) therapy versus insulin-providing (IP) therapy for glycemic control. Results showed similar 5-year mortality in the two glycemic treatment arms. In secondary analyses reported here, we examine the effects of treatment assignment on the incidence of PAD. A total of 1,479 BARI 2D participants with normal ankle-brachial index (ABI) (0.91-1.30) were eligible for analysis. The following PAD-related outcomes are evaluated in this article: new low ABI≤0.9, a lower-extremity revascularization, lower-extremity amputation, and a composite of the three outcomes. RESULTS: During an average 4.6 years of follow-up, 303 participants experienced one or more of the outcomes listed above. Incidence of the composite outcome was significantly lower among participants assigned to IS therapy than those assigned to IP therapy (16.9 vs. 24.1%; P<0.001). The difference was significant in time-to-event analysis (hazard ratio 0.66 [95% CI 0.51-0.83], P<0.001) and remained significant after adjustment for in-trial HbA1c (0.76 [0.59-0.96], P=0.02). CONCLUSIONS: In participants with type 2 diabetes who are free from PAD, a glycemic control strategy of insulin sensitization may be the preferred therapeutic strategy to reduce the incidence of PAD and subsequent outcomes.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".