Design and baseline characteristics of the <scp>AMPLITUDE‐O</scp> cardiovascular outcomes trial of efpeglenatide, a weekly glucagon‐like peptide‐1 receptor agonist
Bibliographic record
Abstract
Abstract Aim The effect of the weekly exendin‐based glucagon‐like peptide‐1 receptor agonist efpeglenatide on cardiovascular (CV) outcomes in high‐risk patients with type 2 diabetes (T2DM) with and without chronic kidney disease (CKD) is unknown. Materials and methods People with T2DM and glycated haemoglobin >7%, ≥18 years old with previous CV disease, or ≥50 years old with CKD [defined as an estimated glomerular filtration rate (eGFR) of 25–59.9 mL/min/1.73 m 2 ], and one or more additional CV risk factors were recruited. Participants were randomized in a 1:1:1 ratio, stratified by current, intended or neither current nor intended use of a sodium‐glucose cotransporter‐2 (SGLT2) inhibitor to receive weekly injections of efpeglenatide (4 mg or 6 mg) or masked placebo. The primary outcome is a major adverse CV event defined as non‐fatal myocardial infarction, non‐fatal stroke or CV death. Secondary outcomes include a composite kidney outcome (new onset macroalbuminuria with an increase from baseline of ≥30%, sustained 40% decrease in eGFR, renal replacement therapy, or sustained eGFR <15 mL/min/1.73 m 2 ). The trial will continue until ≥330 participants have had a major adverse CV event outcome and the sample size was based on accruing enough outcomes to detect non‐inferiority of efpeglenatide versus placebo. Results Recruitment of 4076 participants (33% women, mean age 64.5 years) occurred between 11 May 2018 and 25 April 2019 at 344 sites in 28 countries. Mean baseline glycated haemoglobin was 8.9% (1.5), 31.6% had an eGFR <60 mL/min/1.73 m 2 , 89.5% had previous CV disease and 15.0% were on an SGLT2 inhibitor. Conclusions The results of the AMPLITUDE O trial will inform the use of exendin‐based glucagon‐like peptide‐1 receptor agonist to people with T2DM and high CV risk, with and without CKD, in the presence and absence of an SGLT2 inhibitor.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".