A 24-Week, Randomized, Treat-to-Target Trial Comparing Initiation of Insulin Glargine Once-Daily With Insulin Detemir Twice-Daily in Patients With Type 2 Diabetes Inadequately Controlled on Oral Glucose-Lowering Drugs
Bibliographic record
Abstract
OBJECTIVE: To determine whether glargine is noninferior to detemir regarding the percentage of patients reaching A1C <7% without symptomatic hypoglycemia <or=3.1 mmol/l. RESEARCH DESIGN AND METHODS: In this 24-week trial, 973 insulin-naive type 2 diabetic patients on stable oral glucose-lowering drugs with A1C 7.0-10.5% were randomized to glargine once daily or detemir twice daily. Insulin doses were systematically titrated. RESULTS 27.5 and 25.6% of patients reached the primary outcome with glargine and detemir, respectively, demonstrating the noninferiority of glargine. Improvements in A1C were -1.46 +/- 1.09% for glargine and -1.54 +/- 1.11% for detemir (P = 0.149), with similar proportions of patients achieving A1C <7% (P = 0.254) but more detemir-treated patients reaching A1C <6.5% (P = 0.017). Hypoglycemia risk was similar. Weight gain was higher for glargine (difference: 0.77 kg, P < 0.001). Glargine doses were lower than detemir doses: 43.5 +/- 29.0 vs. 76.5 +/- 50.5 units/day (P < 0.001). CONCLUSIONS: In insulin-naive type 2 diabetic patients, glargine reached similar control as detemir, with more weight gain, but required significantly lower doses.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".