Glucagon in artificial pancreas systems: Potential benefits and safety profile of future chronic use
Bibliographic record
Abstract
The role of glucagon in the pathophysiology of diabetes has long been recognized, although its approved clinical use has so far been limited to the emergency treatment of severe hypoglycaemia. A novel use of glucagon as intermittent mini-boluses is proposed in the dual-hormone version (insulin and glucagon) of the external artificial pancreas. Short-term studies suggest that the incorporation of glucagon into artificial pancreas systems has the potential to further decrease hypoglycaemic risk and improve overall glucose control; however, the potential long-term safety and benefits also need to be investigated given the recognized systemic effects of glucagon. In the present report, we review the available animal and human data on the physiological functions of glucagon, as well as its pharmacological use, according to dosing and duration (acute and chronic). Along with its main role in hepatic glucose metabolism, glucagon affects the cardiovascular, renal, pulmonary and gastrointestinal systems. It has a potential role in weight reduction through its central satiety function and its role in increasing energy expenditure. Most of the pharmacological studies investigating the effects of glucagon have used doses exceeding 1 mg, in contrast to the mini-boluses used in the artificial pancreas. The available data are reassuring but comprehensive human studies using small but chronic glucagon doses that are close to the physiological ranges are lacking. We propose a list of variables that could be monitored during long-term trials of the artificial pancreas. Such trials should address the questions about the risk-benefit ratio of chronic glucagon use.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".