Insulin degludec improves glycaemic control with lower nocturnal hypoglycaemia risk than insulin glargine in basal–bolus treatment with mealtime insulin aspart in Type 1 diabetes (BEGIN<sup>®</sup> Basal–Bolus Type 1): 2‐year results of a randomized clinical trial
Bibliographic record
Abstract
AIMS: The goal of this study was to compare the long-term safety and efficacy of the basal insulin analogue, insulin degludec with insulin glargine (both with insulin aspart) in Type 1 diabetes, over a 2-year time period. METHODS: This open-label trial comprised a 1-year main trial and a 1-year extension. Patients were randomized to once-daily insulin degludec or insulin glargine and titrated to pre-breakfast plasma glucose values of 3.9-4.9 mmol/l. RESULTS: The rate of nocturnal confirmed hypoglycaemia was 25% lower with insulin degludec than with insulin glargine (P = 0.02). Rates of confirmed hypoglycaemia, severe hypoglycaemia and adverse events, and reductions in glycated haemoglobin and fasting plasma glucose were similar between groups. Despite achieving similar glycaemic control, insulin degludec-treated patients used 12% less basal and 9% less total daily insulin than did insulin glargine-treated patients (P < 0.01). CONCLUSIONS: Long-term basal therapy using insulin degludec in Type 1 diabetes required lower doses and was associated with a 25% lower risk for nocturnal hypoglycaemia than insulin glargine.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".