Empagliflozin for the preservation of beta‐cell function in women with recent gestational diabetes: A randomized placebo‐controlled trial
Bibliographic record
Abstract
AIMS: Women with a history of gestational diabetes (GDM) frequently have progressive beta-cell dysfunction, which may result in type 2 diabetes. However, there is a paucity of clinical studies on strategies aiming to preserve beta-cell function in this patient population. This trial evaluated whether empagliflozin can preserve beta-cell function and reduce the prevalence of dysglycemia (prediabetes/diabetes) in women with recent GDM. MATERIALS AND METHODS: We conducted a double-blind, randomized, placebo-controlled trial where 91 women with recent GDM (6-36 months postpartum) were randomized 1:1 to either empagliflozin 10 mg/day or placebo for 48 weeks. Beta-cell function was assessed by Insulin Secretion-Sensitivity Index-2 (ISSI-2) obtained on an oral glucose tolerance test. RESULTS: × Matsuda index also did not differ between the groups. While there was no difference in the secondary outcome of prevalence of dysglycemia at 48 weeks between the arms (empagliflozin 65.7% vs. 48.2% in placebo, p = 0.18), the glucose tolerance worsened in 9.4% of participants in the empagliflozin group as compared to 28% in the placebo group (p = 0.08). CONCLUSIONS: Empagliflozin had no significant effect on beta-cell function in women with recent GDM. Given the sample size evaluated in this trial, the use of SGLT-2 inhibitors warrants further study to elucidate their potential impact on T2DM prevention in women with previous GDM. TRIAL REGISTRATION: Clinicaltrials.gov NCT03215069.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".