Safety and efficacy of <scp>IDegLira</scp> titrated once weekly versus twice weekly in patients with type 2 diabetes uncontrolled on oral antidiabetic drugs: <scp>DUAL VI</scp> randomized clinical trial
Bibliographic record
Abstract
Aims To compare the safety and efficacy of a simpler titration algorithm for insulin degludec/liraglutide ( IDegLira ) with that used in previous DUAL trials in insulin‐naïve patients with type 2 diabetes. Research design and methods This 32‐week, open‐label, non‐inferiority trial randomized adults with type 2 diabetes uncontrolled on metformin ± pioglitazone to receive IDegLira , titrated either once weekly, based on the mean of 2 pre‐breakfast plasma glucose ( PG ) readings (n = 210), or twice weekly, based on the mean of 3 pre‐breakfast PG readings (n = 210). Results Mean HbA1c decreased from 8.2% (65 mmol/mol) to 6.1% (43 mmol/mol) with once‐weekly titration and from 8.1% (65 mmol/mol) to 6.0% (42 mmol/mol) with twice‐weekly titration; non‐inferiority was confirmed (estimated treatment difference: 0.12% [−0.04; 0.28] 95% CI , 1.30 mmol/mol [−0.41; 3.01] 95% CI ). Approximately 90% of patients achieved HbA1c < 7% in each arm. Mean fasting PG was similar after 32 weeks. Weight change was −1.0 kg vs −2.0 kg for once‐weekly vs twice‐weekly titration. Rates of severe or blood glucose‐confirmed symptomatic hypoglycaemia were low in both arms: 0.16 events/patient‐year of exposure ( PYE ) for once‐weekly, 0.76 events/ PYE for twice‐weekly titration. Mean IDegLira dose at 32 weeks was 41 dose steps (41 U IDeg /1.48 mg L ira) for both arms. Overall adverse event rates were 207.8 and 241.3 events/100 PYE with once‐weekly and twice‐weekly titration, respectively. Conclusion A pragmatic titration algorithm with once‐weekly adjustments based on 2 PG readings resulted in a safety and glycaemic efficacy profile similar to that with twice‐weekly adjustments based on 3 preceding PG values in insulin‐naïve patients.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".