Duration of diabetes and cardiorenal efficacy of liraglutide and semaglutide: A post hoc analysis of the LEADER and SUSTAIN 6 clinical trials
Bibliographic record
Abstract
Cardiovascular risk reduction with liraglutide and semaglutide in patients with type 2 diabetes was demonstrated in the LEADER (ClinicalTrials.gov: NCT01179048) and SUSTAIN 6 (ClinicalTrials.gov: NCT01720446) cardiovascular outcome trials. This post hoc analysis assessed the impact of diabetes duration (<5, 5 to <15, 15 to <25 and ≥25 years at baseline) on cardiorenal efficacy of these human glucagon-like peptide-1 analogues using a Cox proportional hazards model. Proportions of patients in the LEADER trial across diabetes duration strata were 15% (<5 years, n = 1377), 50% (5 to <15 years, n = 4692), 27% (15 to <25 years, n = 2504) and 8% (≥25 years, n = 748); corresponding proportions in the SUSTAIN-6 trial were 13% (<5 years, n = 422), 48% (5 to <15 years, n = 1582), 30% (15 to <25 years, n = 977) and 10% (≥25 years, n = 316). Overall, longer diabetes duration was associated with higher age; higher prevalence of females; history of ischaemic stroke, peripheral arterial disease and insulin use; and inferior renal function. There was an increased frequency of major adverse cardiovascular events (MACE), expanded MACE and nephropathy events with increasing diabetes duration. Liraglutide and semaglutide consistently reduced the risk of cardiorenal outcomes across categories of diabetes duration (P-interaction was not significant for all endpoints analysed).
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".