Flexibly timed once‐daily dosing with degludec: a new ultra‐long‐acting basal insulin
Bibliographic record
Abstract
Insulin treatment in type 1 and type 2 diabetes (T1D and T2D) is highly efficacious, but in practice, non-adherence and ineffective dose titration limit its effectiveness. Barriers to more effective insulin treatment are numerous, including hypoglycaemia, fear of hypoglycaemia and concern about weight gain. The regular treatment timing needed with conventional basal insulins [neutral protamine Hagedorn (NPH) insulin and the first-generation analogues glargine and detemir] may also make adherence to these treatments problematic for many patients. Indeed, surveys indicate that the rigidity of this schedule induces some patients with T1D and T2D to omit insulin doses. Degludec is a novel, ultra-long-acting basal insulin analogue that is as effective as insulin glargine, but significantly reduces patients' risk of nocturnal hypoglycaemia. Because of its peakless, extended and highly predictable glucose-lowering effect, once-daily dosing on a flexible schedule may be feasible with degludec. Studies testing this possibility suggest that degludec tolerates day-to-day variation in dose timing while maintaining full efficacy and low risk of nocturnal hypoglycaemia. Degludec would appear to be an appropriate choice for patients being considered for a basal analogue, and it may be particularly well suited to patients with unpredictable social or work schedules, those who travel frequently and those who find rigid scheduling of their insulin injections a burden or barrier to regular treatment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".