Efficacy and Safety of Dulaglutide in Older Patients: A post hoc Analysis of the REWIND trial
Bibliographic record
Abstract
CONTEXT: Dulaglutide reduced major adverse cardiovascular events (MACE) in the Researching Cardiovascular Events with a Weekly INcretin in Diabetes (REWIND) trial. Its efficacy and safety in older vs younger patients have not been explicitly analyzed. OBJECTIVE: This work aimed to assess efficacy and safety of dulaglutide vs placebo in REWIND by age subgroups (≥ 65 and < 65 years). METHODS: A post hoc subgroup analysis of REWIND was conducted at 371 sites in 24 countries. Participants included type 2 diabetes patients aged 50 years or older with established cardiovascular (CV) disease or multiple CV risk factors, and a wide range of glycemic control. Patients were randomly assigned (1:1) to dulaglutide 1.5 mg or placebo as an add-on to country-specific standard of care. Main outcomes measures included MACE (first occurrence of the composite of nonfatal myocardial infarction, nonfatal stroke, or death from CV or unknown causes). RESULTS: There were 5256 randomly assigned patients who were 65 years or older (mean = 71.0), and 4645 were younger than 65 years (mean = 60.7). Baseline characteristics were similar in randomized treatment groups. Dulaglutide treatment showed a similar reduction in the incidence (11% vs 13%) of MACE in older vs younger patients. The rate of permanent study drug discontinuation, incidence of all-cause mortality, hospitalizations for heart failure, severe hypoglycemia, severe renal or urinary events, and serious gastrointestinal events were similar between randomized treatment groups within each age subgroup. The incidence rate of serious cardiac conduction disorders was numerically higher in the dulaglutide group compared to placebo within each age subgroup but the difference was not statistically significant. CONCLUSION: Dulaglutide had similar efficacy and safety in REWIND in patients65 years and older and those younger than 65 years.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".