One‐year efficacy and safety of saxagliptin add‐on in patients receiving dapagliflozin and metformin
Bibliographic record
Abstract
AIMS: Greater reductions in glycated haemoglobin (HbA1c) with saxagliptin, a dipeptidyl peptidase-4 inhibitor, versus placebo add-on in patients with type 2 diabetes who had inadequate glycaemic control with dapagliflozin 10 mg/d plus metformin were demonstrated after 24 weeks of treatment. Results over 52 weeks of treatment were assessed in this analysis. MATERIALS AND METHODS: Patients (mean baseline HbA1c 7.9%) receiving open-label dapagliflozin 10 mg/d plus metformin were randomized to double-blind saxagliptin 5 mg/d or placebo add-on. RESULTS: The adjusted mean change from baseline to week 52 in HbA1c was greater with saxagliptin than with placebo add-on -0.38% vs 0.05%; difference -0.42% (95% confidence interval -0.64, -0.20)]. More patients achieved the HbA1c target of <7% with saxagliptin than with placebo add-on (29% vs 13%), and fewer patients were rescued or discontinued the study for lack of glycaemic control with saxagliptin than with placebo add-on (19% vs 28%). Reductions from baseline in body weight (≤1.5 kg) occurred in both groups. Similar proportions of patients reported ≥1 adverse event with saxagliptin (58.2%) and placebo add-on (58.0%); no new safety signals were detected. Hypoglycaemia was infrequent in both treatment groups (≤2.5%), with no major episodes. The rate of urinary tract infections was similar in the saxagliptin and placebo add-on groups (7.8% vs 7.4%). The incidence of genital infections was 3.3% with saxagliptin versus 6.2% with placebo add-on. CONCLUSIONS: Triple therapy with saxagliptin add-on to dapagliflozin plus metformin for 52 weeks resulted in sustained improvements in glycaemic control without an increase in body weight or increased risk 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".