The metabolic effects of adding exenatide to basal insulin therapy when targeting remission in early type 2 diabetes in a randomized clinical trial
Bibliographic record
Abstract
Combining a glucagon-like peptide-1 receptor agonist (GLP1-RA) with basal insulin is an emerging option when initiating injectable therapy in longstanding type 2 diabetes (T2DM). Recognizing that short-term insulin therapy can improve beta-cell function and induce glycemic remission in early T2DM, we hypothesized that adding the short-acting GLP1-RA exenatide to basal insulin in early T2DM may enhance the achievability of these outcomes. In this completed, 20-week, open-label, parallel-arm trial at an academic hospital, 103 individuals aged 30-80 years with <7 years duration of T2DM were randomized (by computer-generated sequence) to 8-weeks treatment with (i) insulin glargine (Glar; n = 33), (ii) glargine + thrice-daily lispro (Glar/Lispro; n = 35), or (iii) glargine + twice-daily exenatide (Glar/Exenatide; n = 35), followed by 12-weeks washout. The analyzed population of 102 participants (median 3.5 years of T2DM, A1c 6.6% ±0.7%) consisted of 33 on Glar, 35 on Glar/Lispro and 34 on Glar/Exenatide. Oral glucose tolerance tests at baseline, 4-weeks, 8-weeks and 20-weeks enabled assessment of beta-cell function (Insulin Secretion-Sensitivity Index-2 (ISSI-2)) and glycemic control. Mean ISSI-2 over the 8-week intervention (primary outcome) did not differ across the groups (Glar/Exenatide 237 ± 11; Glar/Lispro 208 ± 11; Glar 223 ± 11; p = 0.19). Baseline-adjusted A1c at 8-weeks (secondary outcome) was lowest in Glar/Exenatide followed by Glar/Lispro and Glar (mean 5.9% vs 6.0% vs 6.2%; p = 0.0007). After 12-weeks washout, however, neither baseline-adjusted A1c nor baseline-adjusted ISSI-2 (secondary outcomes) differed between the groups, nor did (additional outcome) rates of remission (Glar/Exenatide 26.7%, Glar/Lispro 43.8%, Glar 32.1%; p = 0.35). There were no severe hypoglycemia episodes. In conclusion, adding exenatide to basal insulin in early T2DM does not further enhance underlying beta-cell function or the capacity to achieve diabetes remission, despite yielding on-treatment glycemic benefit.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| 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".