The Future of Combination Therapies of Insulin with a Glucagon-like Peptide-1 Receptor Agonists in Type 2 Diabetes – Is it Advantageous?
Bibliographic record
Abstract
Safe and effective therapies for type 2 diabetes are needed to reduce the burden of late complications and costs associated with this chronic disease. Hypoglycaemia and body weight gain are side effects and limitations of the therapy with insulin and/or sulphonylureas. Recently, the combination of glucagon-like peptide-1 (GLP-1) receptor agonists and insulin has become available, which is associated with good efficacy and less risk for hypoglycaemia and weight gain. This editorial discusses the strategies to escalate treatment in type 2 diabetes in view of this novel combination and discusses its placement within the therapeutic algorithm of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Recent developments to simplify this combination therapy are also dealt with.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".