Hypoglycaemia risk with insulin degludec compared with insulin glargine in type 2 and type 1 diabetes: a pre‐planned meta‐analysis of phase 3 trials
Why this work is in the frame
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Bibliographic record
Abstract
AIM: Hypoglycaemia and the fear of hypoglycaemia are barriers to achieving normoglycaemia with insulin. Insulin degludec (IDeg) has an ultra-long and stable glucose-lowering effect, with low day-to-day variability. This pre-planned meta-analysis aimed to demonstrate the superiority of IDeg over insulin glargine (IGlar) in terms of fewer hypoglycaemic episodes at equivalent HbA1c in type 2 and type 1 diabetes mellitus (T2DM/T1DM). METHODS: Pooled patient-level data for self-reported hypoglycaemia from all seven (five in T2DM and two in T1DM) randomized, controlled, phase 3a, treat-to-target trials in the IDeg clinical development programme comparing IDeg once-daily (OD) vs. IGlar OD were analysed. RESULTS: Four thousand three hundred and thirty subjects (2899 IDeg OD vs. 1431 IGlar OD) were analysed. Among insulin-naïve T2DM subjects, significantly lower rates of overall confirmed, nocturnal confirmed and severe hypoglycaemic episodes were reported with IDeg vs. IGlar: estimated rate ratio (RR):0.83[0.70;0.98](95%) (CI) , RR:0.64[0.48;0.86](95%) (CI) and RR:0.14[0.03;0.70](95%) (CI) . In the overall T2DM population, significantly lower rates of overall confirmed and nocturnal confirmed episodes were reported with IDeg vs. IGlar [RR:0.83[0.74;0.94](95%) (CI) and RR:0.68[0.57;0.82](95%) (CI) ). In the T1DM population, the rate of nocturnal confirmed episodes was significantly lower with IDeg vs. IGlar during maintenance treatment (RR:0.75[0.60;0.94](95%) (CI) ). Reduction in hypoglycaemia with IDeg vs. IGlar was more pronounced during maintenance treatment in all populations. CONCLUSIONS: The limitations of this study include the open-label design and exclusion of subjects with recurrent severe hypoglycaemia. This meta-analysis confirms that similar improvements in HbA1c can be achieved with fewer hypoglycaemic episodes, particularly nocturnal episodes, with IDeg vs. IGlar across a broad spectrum of patients with diabetes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it