Safety and Efficacy of Dulaglutide, a Once Weekly GLP-1 Receptor Agonist, for the Management of Type 2 Diabetes
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes (T2D) is an increasingly common endocrine disorder that is characterized by chronic hyperglycemia and tissue compartment abnormalities, including macrovascular and microvascular complications. More than 90% of patients with T2D will be diagnosed and treated in the primary care setting. One of the relatively recent additions to the increasing array of approved antidiabetic medications is the glucagon-like peptide-1 receptor agonist class. Mechanisms of action for glucagon-like peptide-1 receptor agonists include: 1) stimulation of insulin secretion through β-cells, though only when glucose levels are elevated (hence, minimizing risk for hypoglycemia); 2) blunting of glucagon secretion; 3) increased satiety; and 4) decreased rate of release of gastric contents into the small intestine, thereby reducing glycemic load. Recent T2D treatment guidelines encourage individualization of therapy. Many patients still do not achieve optimal glycemic control. Therefore, other treatment options are important. METHODS: A literature search was performed using PubMed and MEDSCAPE to retrieve abstracts and articles pertinent to topics discussed in this review. Original research articles, reviews, and clinical trial manuscripts were identified based on relevance. Only English language articles were considered. Results In 3 phase 3 registration trials in patients with T2D, once-weekly dulaglutide demonstrated superior efficacy at the primary endpoint to metformin as monotherapy, to sitagliptin as add-on to metformin, and to exenatide twice daily as add-on to metformin and pioglitazone. The safety profile of dulaglutide in these trials is similar to currently available glucagon-like peptide-1 receptor agonists, characterized predominantly by gastrointestinal symptoms (ie, nausea, vomiting, and diarrhea). Based on these results, once-weekly dulaglutide should be a relevant additional treatment option for the management of T2D.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| 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".