The effect of basal–bolus therapy varies with baseline 1,5‐anhydroglucitol level in people with Type 2 diabetes: a <i>post hoc</i> analysis
Bibliographic record
Abstract
Abstract Aims To investigate the impact of baseline 1,5‐anhydroglucitol on the treatment effect of basal–bolus therapy in people with Type 2 diabetes. Methods Post hoc analysis of onset 3, an 18‐week, randomized, phase 3 trial evaluating the efficacy and safety of fast‐acting insulin aspart in basal–bolus therapy (n = 116) vs. basal insulin‐only therapy (n = 120) in people with Type 2 diabetes. The estimated treatment difference in change from baseline in HbA1c was investigated for different cut‐off values of baseline 1,5‐anhydroglucitol (2, 3, 4, 5 and 6 μg/ml). Results The estimated treatment difference in change from baseline in HbA1c between basal–bolus therapy and basal insulin‐only therapy was statistically significantly greater in participants with baseline 1,5‐anhydroglucitol ≤3 μg/ml (n = 34) vs. >3 μg/ml (n = 198) [estimated treatment difference (95% CI): −1.53% (−2.12; −0.94) vs. −0.82% (−1.07; −0.57); P‐value for interaction = 0.03]. The estimated treatment difference became more pronounced when comparing participants with 1,5‐anhydroglucitol ≤2 μg/ml (n = 15) vs. >2 μg/ml (n = 217) [estimated treatment difference (95% CI): −2.26% (−3.15; −1.36) vs. −0.85% (−1.08; −0.62); P‐value for interaction = 0.003]. For cut‐off values ≥4 μg/ml, estimated treatment differences were numerically greater below the cut‐off compared with above, although the interaction terms were not statistically significant. Conclusion This analysis indicates that people with Type 2 diabetes with low 1,5‐anhydroglucitol have an added treatment benefit with basal–bolus therapy compared with people with higher 1,5‐anhydroglucitol. Further research is needed to clarify any clinical utility of these findings. Clinical Trials Registry No: NCT01850615
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.014 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".