Dulaglutide and incident atrial fibrillation or flutter in patients with type 2 diabetes: A post hoc analysis from the <scp>REWIND</scp> randomized trial
Bibliographic record
Abstract
AIM: To assess the occurrence of atrial fibrillation or atrial flutter (atrial arrhythmias [AA]) in patients with type 2 diabetes treated with once-weekly subcutaneous dulaglutide versus placebo. MATERIALS AND METHODS: Patients without electrocardiographic (ECG)-confirmed AA at baseline and randomized in the REWIND trial were assessed for the development of AA based on an annual ECG. Additional analyses included whether dulaglutide compared with placebo reduced the composite outcome of AA or death, AA or cardiovascular death, AA or stroke and AA or heart failure. RESULTS: Among 9543 participants (mean age 66 ± 7 years, with cardiovascular risk factors and 31% with previous cardiovascular disease) without AA at entry in the trial, 524 patients (5.5%) had at least one episode of AA during the median 5.4 years of follow-up. Incident AA occurred in 269 of the 4769 participants allocated to dulaglutide (5.6%), at a rate of 10.7 per 1000 person-years, versus 255 of the 4774 allocated to placebo (5.3%), at a rate of 10.5 per 1000 person-years (P = .59). There was also no effect of dulaglutide on the composite outcome of AA and death or AA and heart failure. CONCLUSION: This post hoc analysis of data from the REWIND trial showed that treatment with dulaglutide was not associated with a reduced incidence of AA in this at-risk group of patients with type 2 diabetes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| 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) | 0.003 | 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".