911-P: Effect of Dapagliflozin on Blood and Breath Ketones during Supervised Insulin Withdrawal in Adults with Type 1 Diabetes
Bibliographic record
Abstract
Introduction: SGLT2 inhibitors increase DKA risk, limiting their use in T1D. To understand the effect of SGLT2i on ketone production, we measured glucose, beta-hydroxybutyrate (BOHB) and breath acetone (BrACE) with and without dapagliflozin during supervised insulin withdrawal in adults with T1D. Methods: 20 adults with T1D underwent on-site supervised insulin withdrawal twice in a randomized crossover design: during usual care and after treatment with dapagliflozin (10 mg daily for 2 weeks plus the test day). After insulin withdrawal, capillary blood glucose, BOHB, and BrACE measurements were obtained at least hourly until stopping rules were met (glucose >400 mg/dL, BOHB >3 mmol/L, >8 hours elapsed, or participant request). Results: Mean (± SD) age was 48 ± 18 years, with baseline HbA1c 7.0 ± 0.9%. The maximal BOHB and BrACE values achieved during supervised insulin withdrawal were both greater with dapagliflozin than usual care (BOHB: 2.4 ± 1.2 vs. 1.6 ± 1.0 mmol/L, P <0.001; BrACE: 13.7 ± 7.5 vs. 8.7 ± 5.7, P = 0.004). Adjusted for time from insulin withdrawal, dapagliflozin treatment was associated with significantly greater BOHB and BrACE concentration (both P <0.001 by ANCOVA). The proportions of participants reaching BOHB >1.5 mmol/L and >2.5 mmol/L during supervised insulin withdrawal were greater in the dapagliflozin arm (74% vs. 37% with BOHB >1.5 mmol/L; 53% vs. 16% with BOHB >2.5 mmol/L; both P <0.05 by McNemar’s test). Blood glucose reached a lower maximum (218 ± 53 vs. 302 ± 58 mg/dL, P <0.001) in the dapagliflozin arm and did not significantly change during insulin withdrawal in the dapagliflozin arm (P for linear trend = 0.91). Conclusion: In adults with T1D undergoing up to 8 hours of supervised insulin withdrawal after dapagliflozin treatment, blood and breath ketone concentrations were significantly greater compared to usual care and in the absence of significant hyperglycemia. Disclosure M.C. Petersen: None. K.E. Jones: None. K.L. Bohnert: None. A.M. Markov: None. M. Salam: None. P. Krutilova: None. A.M. McKee: Advisory Panel; Medtronic, Novo Nordisk. Employee; Novo Nordisk. S.E. Adamson: None. J.B. McGill: Advisory Panel; Bayer Inc., Boehringer-Ingelheim, ClearNote Health, Lilly Diabetes, MannKind Corporation, Novo Nordisk. Research Support; Novo Nordisk. Funding JDRF (2-SRA-2022-1190-M-B)
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".