Evaluating the Effectiveness of Switching to Insulin Degludec from Other Basal Insulins in a Real-World Canadian Population with Type 1 or Type 2 Diabetes: The CAN-TREAT Study
Bibliographic record
Abstract
The aim of the study was to examine glycaemic control and safety of insulin degludec (degludec) in patients with either type 1 diabetes (T1D) or type 2 diabetes (T2D) under routine care settings in Canada. Data were extracted from medical records of adults with T1D or T2D who switched to degludec (± prandial insulin) from another basal insulin (± prandial insulin) ≥ 6 months prior to data collection. The primary endpoint was change in glycated haemoglobin (HbA 1c ) at 6 ± 3 months after degludec initiation. Secondary endpoints included change in hypoglycaemia rate in the 6 months before versus the 6 months after switching, and change in mean total daily insulin dose. Of 667 patients assessed for eligibility, 626 were included. After 6 ± 3 months, HbA 1c decreased from baseline in patients with T1D (− 0.3% [− 0.42, − 0.14] 95% CI ; p < 0.001) and in patients with T2D (− 0.4% [− 0.55, − 0.30] 95% CI ; p < 0.001). In patients with T1D, there were significant reductions in the rates of overall (rate ratio [RR] 0.70), non-severe (RR 0.69), non-severe nocturnal (RR 0.36), and severe nocturnal hypoglycaemia (RR 0.12; all p ≤ 0.004). In patients with T2D there was a significant reduction in non-severe nocturnal hypoglycaemia (RR 0.22; p < 0.001). Mean daily basal insulin dose decreased in patients with T1D (− 1.6 units [− 2.8, − 0.4] 95% CI ; p = 0.008); there was no significant change in patients with T2D (− 0.6 units [− 2.7, 1.4] 95% CI ; p = 0.543). In routine clinical practice, improved glycaemic control was observed in patients with T1D or T2D switching to insulin degludec from other basal insulins, with either improvement or no change in hypoglycaemia rates. ClinicalTrials.gov NCT03674866
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".