Dulaglutide 1.5 mg as an add‐on option for patients uncontrolled on insulin: Subgroup analysis by age, duration of diabetes and baseline glycated haemoglobin concentration
Bibliographic record
Abstract
AIMS: To assess efficacy and safety of dulaglutide 1.5 mg combined with insulin, categorized by subgroups of baseline glycated haemoglobin (HbA1c; ≤9% and >9% [≤74.9 and >74.9 mmol/mol]), age (<65 and ≥65 years), and duration of diabetes (<10 and ≥10 years) at 6 months in patients with type 2 diabetes (T2D). MATERIALS AND METHODS: This pooled analysis was conducted in a population of patients with T2D with similar baseline characteristics who were included in the AWARD-4 and AWARD-9 clinical trials and randomized to dulaglutide 1.5 mg (pooled mean baseline age 59 years, duration of diabetes 13 years, HbA1c 8.4% [68.3 mmol/mol]). Weight and hypoglycaemia were analysed by individual trial. In AWARD-4, dulaglutide plus lispro three times daily was assessed against glargine plus lispro three times daily. In AWARD-9, dulaglutide added to glargine was assessed against placebo added to glargine. Insulins were titrated to target in both trials. RESULTS: A total of 445 patients were included in this analysis (73% with HbA1c ≤9%, 27% [≤74.9 mmol/mol] with HbA1c >9% [>74.9 mmol/mol]; 70% aged <65 years, 30% aged ≥65 years; 36% with duration of diabetes <10 years, 64% with duration of diabetes ≥10 years). At 6 months, dulaglutide 1.5 mg significantly reduced HbA1c in all subgroups (P < .001), with the highest reduction observed in patients with baseline HbA1c >9% (>74.9 mmol/mol) (range - 1.3% to -2.5% [-14.2 to -27.3 mmol/mol]). The incidence rates of documented symptomatic and severe hypoglycaemia were similar in all subgroups in both trials. The most common adverse events observed in each trial were gastrointestinal in nature. CONCLUSION: Dulaglutide 1.5 mg combined with basal or prandial insulin is efficacious for patients with T2D irrespective of age, duration of diabetes or baseline HbA1c.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".