Glucose Exposure and Variability with Empagliflozin as Adjunct to Insulin in Patients with Type 1 Diabetes: Continuous Glucose Monitoring Data from a 4-Week, Randomized, Placebo-Controlled Trial (EASE-1)
Bibliographic record
Abstract
BACKGROUND: We evaluated the effect of empagliflozin as adjunct to insulin on 24-h glucose exposure and variability in patients with type 1 diabetes. METHODS: ≥7.5% to ≤10.5% were randomized to receive empagliflozin 2.5 mg, empagliflozin 10 mg, empagliflozin 25 mg, or placebo once daily as adjunct to insulin for 4 weeks. Insulin dose was to be kept as stable as possible during week 1 of treatment and was freely adjustable thereafter. Markers of glucose exposure and variability were assessed from 7-day blinded continuous glucose monitoring intervals. This study is completed ( ClinicalTrials.gov NCT01969747). RESULTS: Empagliflozin reduced hourly mean glucose area under the median curve over 24 h versus placebo within week 1 (adjusted mean differences: -12.2 mg/dL·h [95% confidence interval -23.9 to -0.5], -30.2 mg/dL·h [-42.2 to -18.2], and -33.0 mg/dL·h [-44.8 to -21.1] with empagliflozin 2.5, 10, and 25 mg, respectively; all P < 0.05) and increased time in glucose target range (>70 to ≤180 mg/dL). Results were sustained to week 4 with empagliflozin 25 mg. All empagliflozin doses significantly reduced glucose variability (interquartile range and mean amplitude of glucose excursions) versus placebo at weeks 1 and 4. Except for small increases in hours per day with glucose ≤70 mg/dL during the stable insulin period, empagliflozin did not increase time in hypoglycemia compared with placebo. CONCLUSIONS: In patients with type 1 diabetes, empagliflozin as adjunct to insulin decreased glucose exposure and variability and increased time in glucose target range.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".