Low-Dose Empagliflozin as Adjunct to Hybrid Closed-Loop Insulin Therapy in Adults With Suboptimally Controlled Type 1 Diabetes: A Randomized Crossover Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: To assess whether low doses of empagliflozin as adjunct to hybrid closed-loop therapy improve glycemia compared with placebo in adults with type 1 diabetes (T1D) who are not able to achieve targets with the system alone. RESEARCH DESIGN AND METHODS: A double-blind crossover randomized controlled trial was performed in adults with suboptimally controlled T1D (HbA1c 7.0-10.5%) who were not able to achieve a target time in range (3.9-10.0 mmol/L) ≥70% after 14 days of hybrid closed-loop therapy. Three 14-day interventions were performed with placebo, 2.5 mg empagliflozin, or 5 mg empagliflozin as adjunct to the McGill artificial pancreas. Participants were assigned at a 1:1:1:1:1:1 ratio with blocked randomization. The primary outcome was time in range (3.9-10.0 mmol/L). Analysis was by intention to treat, and a P value <0.05 was regarded as significant. RESULTS: A total of 24 participants completed the study (50% male; age 33 ± 14 years; HbA1c 8.1 ± 0.5%). The time in range was 59.0 ± 9.0% for placebo, 71.6 ± 9.7% for 2.5 mg empagliflozin, and 70.2 ± 8.0% for 5 mg empagliflozin (P < 0.0001 between 2.5 mg empagliflozin and placebo and between 5 mg empagliflozin and placebo). Mean daily capillary ketone levels were not different between arms. There were no serious adverse events or cases of diabetic ketoacidosis or severe hypoglycemia in any intervention. CONCLUSIONS: Empagliflozin at 2.5 and 5 mg increased time in range during hybrid closed-loop therapy by 11-13 percentage points compared with placebo in those who otherwise were unable to attain glycemic targets. Future studies are required to assess long-term efficacy and safety.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".