Effects of basal insulin glargine and omega‐3 on lower limb arterial disease outcome in patients with dysglycaemia: An analysis of the Outcome Reduction with an Initial Glargine INtervention (ORIGIN) trial
Bibliographic record
Abstract
The impact of insulin or omega-3 supplements on the incidence and progression of peripheral artery disease (PAD) in patients with dysglycaemia has not been well studied. The Outcome Reduction with an Initial Glargine INtervention (ORIGIN) trial randomized participants with dysglycaemia and cardiovascular risk factors to titrated insulin glargine vs standard care, and to either 1 g of omega-3 per day or placebo. We assessed incident PAD, defined as the composite of either asymptomatic or symptomatic PAD according to the randomized interventions in the 11 119 ORIGIN participants whose baseline ankle-brachial index (ABI) was >0.9 (no PAD), and PAD progression in the 971 ORIGIN participants whose baseline ABI was ≤0.9. Hazard ratios (HR) were adjusted for confounders. During a 6.2-year follow-up period, allocation to insulin glargine vs standard care had a neutral effect on the composite of PAD incidence (HR, 0.99; 95% CI, 0.86-1.15) and progression (HR, 0.88; 95% CI, 0.63-1.22). Similar findings were noted for allocation to omega-3 vs placebo for PAD incidence (HR, 1.02; 95% CI, 0.89-1.18) and progression (HR, 0.93; 95% CI, 0.67-1.28). In this large study, neither insulin glargine nor omega-3 affected the incidence or progression of PAD.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".