CANadian CAnagliflozin REgistry: Effectiveness and safety of canagliflozin in the treatment of type 2 diabetes mellitus in Canadian clinical practice
Bibliographic record
Abstract
Aim There is limited information concerning the effects of canagliflozin (CANA), a sodium‐glucose co‐transporter 2 inhibitor (SGLT2i) in a real‐world clinical setting in Canada. CanCARE is a 12‐month, prospective, observational analysis to demonstrate the effectiveness and safety of CANA in usual clinical practice in Canada. Materials and methods SGLT2i‐naïve adult patients with type 2 diabetes mellitus (T2DM) (n = 527) on a stable antihyperglycemic agent (AHA) regimen with glycated hemoglobin (A1C) ≥ 7%, an estimated glomerular filtration rate (eGFR) ≥ 60 mL/min/1.73m 2 , were initiated on CANA as part of their usual treatment approach, and were followed for a period of 12 months. The primary effectiveness objective was the mean change in HbA1c from baseline to 6 and 12 months. Results Significant improvement from baseline in mean HbA1c levels were observed at 6 months (−0.90%; 95% CI, −1.02, −0.78) and at 12 months (−1.04%; 95% CI, −1.15, −0.92), regardless of duration of diabetes or background AHA treatment regimen. Similarly, significant decreases in systolic blood pressure (−4.65 mm Hg); body weight (−3.24 kg), waist circumference (−2.91 cm) and body mass index (−1.15 kg/m 2 ) were observed at 12 months. Additionally, 40.5% of patients achieved the double endpoint (≥0.5% HbA1c reduction and ≥ 3% weight loss), while 24.3% of patients achieved the triple composite endpoint (≥0.5% HbA1c reduction, ≥3% weight loss and ≥ 4 mm Hg systolic blood pressure reduction). No unexpected adverse events were reported. Conclusion CANA provided sustained clinically meaningful improvements in cardiometabolic parameters in this study in a real‐world setting, confirming findings from randomized controlled trials.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".