Semaglutide once weekly in people with type 2 diabetes: Real‐world analysis of the Canadian <scp>LMC</scp> diabetes registry ( <scp>SPARE</scp> study)
Bibliographic record
Abstract
AIMS: To investigate real-world short-term clinical outcomes in adults with type 2 diabetes (T2D) who initiated semaglutide in a specialist endocrinology practice in Canada. MATERIALS AND METHODS: This study was a retrospective observational study using data from the Canadian LMC Diabetes Registry. Adults with T2D who were naïve to glucagon-like peptide-1 receptor agonist (GLP-1RA) therapy, initiated semaglutide therapy as usual standard of care between February 2018 and February 2019, and maintained semaglutide therapy during follow-up, were eligible for analysis. The primary outcome was mean change in glycated haemoglobin (HbA1c) at 3- to 6-month follow-up. RESULTS: In the final analytical cohort (n = 937), there was a statistically significant mean ± SD reduction in HbA1c of -1.03 ± 1.24% (11.3 ± 13.6 mmol/mol, P < 0.001) and weight of -3.9 ± 4.0 kg (P < 0.001), with no significant change in self-reported incidence of hypoglycaemia. There was a significant reduction in HbA1c and weight regardless of number of co-therapies or semaglutide dose. However, adults using the 1.0-mg dose had a significantly greater reduction in HbA1c compared to adults using the 0.25- to 0.5-mg dose (between-group difference - 0.24 ± 0.06%, 2.6 ± 0.7 mmol/mol; P < 0.001). Adults using basal-bolus therapy required a significantly lower median total daily dose of insulin after adding semaglutide (0.82 vs. 0.93 U/kg; P < 0.001). CONCLUSIONS: This retrospective observational study demonstrated that GLP-1RA-naïve adults with T2D initiating semaglutide in a real-world clinical practice had a statistically and clinically significant reduction in HbA1c and body weight after 3 to 6 months, regardless of semaglutide dose or order of semaglutide therapy, with no significant change in reported incidence of hypoglycaemia.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".