Insulin Degludec Versus Insulin Glargine in Insulin-Naive Patients With Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To compare ultra-long-acting insulin degludec with glargine for efficacy and safety in insulin-naive patients with type 2 diabetes inadequately controlled with oral antidiabetic drugs (OADs). RESEARCH DESIGN AND METHODS: In this 1-year, parallel-group, randomized, open-label, treat-to-target trial, adults with type 2 diabetes with A1C of 7-10% taking OADs were randomized 3:1 to receive once daily degludec or glargine, both with metformin. Insulin was titrated to achieve prebreakfast plasma glucose (PG) of 3.9-4.9 mmol/L. The primary end point was confirmation of noninferiority of degludec to glargine in A1C reduction after 52 weeks in an intent-to-treat analysis. RESULTS: In all, 1,030 participants (mean age 59 years; baseline A1C 8.2%) were randomized (degludec 773, glargine 257). Reduction in A1C with degludec was similar (noninferior) to that with glargine (1.06 vs. 1.19%), with an estimated treatment difference of degludec to glargine of 0.09% (95% CI -0.04 to 0.22). Overall rates of confirmed hypoglycemia (PG <3.1 mmol/L or severe episodes requiring assistance) were similar, with degludec and glargine at 1.52 versus 1.85 episodes/patient-year of exposure (PYE). There were few episodes of nocturnal confirmed hypoglycemia in the overall population, and these occurred at a lower rate with degludec versus glargine (0.25 vs. 0.39 episodes/PYE; P = 0.038). Similar percentages of patients in both groups achieved A1C levels <7% without hypoglycemia. End-of-trial mean daily insulin doses were 0.59 and 0.60 units/kg for degludec and glargine, respectively. Adverse event rates were similar. CONCLUSIONS: Insulins degludec and glargine administered once daily in combination with OADs provided similar long-term glycemic control in insulin-naive patients with type 2 diabetes, with lower rates of nocturnal hypoglycemia with degludec.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".