HbA1c Reduction in Dulaglutide-Treated Patients Irrespective of Duration of Diabetes, Microvascular Disease, and BMI: A Post Hoc Analysis From the REWIND Trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate participant characteristics and long-term changes in glycated hemoglobin (HbA1c) levels in patients treated with dulaglutide 1.5 mg in a post hoc analysis of the Researching cardiovascular Events with a Weekly INcretin in Diabetes (REWIND) trial. RESEARCH DESIGN AND METHODS: Change from baseline in HbA1c was assessed during and up to 72 months of treatment before and after adjustment for duration of diabetes, prior microvascular disease (nephropathy or retinopathy), and BMI. Slope analyses were used to assess the change in HbA1c during 0-12 months and 12-72 months of therapy. RESULTS: HbA1c was significantly reduced in patients treated with dulaglutide compared with placebo during 72 months of treatment (least-squares mean difference = -0.61%, P < 0.001), regardless of diabetes duration, prior microvascular disease, and BMI (all interaction P > 0.07). Significant reductions were apparent at all time points and were independent of these baseline characteristics. Slope analyses revealed that the dulaglutide group experienced a higher rate of HbA1c reduction compared with the placebo group from 0 to 12 months before and after adjustment. The dulaglutide group also experienced a higher rate of HbA1c increase from 12 to 72 months compared with the placebo group that became nonsignificant after adjustment for diabetes duration, prior microvascular disease, and BMI combined. Despite the greater rate of HbA1c increase in the dulaglutide group during this period, mean HbA1c values remained below baseline in the dulaglutide group and below mean HbA1c values in the placebo group. CONCLUSIONS: Dulaglutide 1.5-mg treatment was statistically associated with a long-lasting decrease in HbA1c over 72 months, irrespective of baseline duration of diabetes, microvascular disease, and BMI.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| 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".