106-LB: Postprandial Glucose Management among Adults Living with Type 1 Diabetes Using Single-Hormone and Dual-Hormone Automated Insulin Delivery Systems
Bibliographic record
Abstract
Introduction: Despite the rapid advances of diabetes technologies, postprandial glucose management remains a challenge for people living with type 1 diabetes (pwT1D). We aim to assess the efficacy of single-hormone (SH) compared to dual-hormone (DH) automated insulin delivery (AID) systems in postprandial glucose management. Methods: Post-hoc analysis of a randomized controlled crossover inpatient trial including three standardized meals (taken at 8am, 12 pm, and 5pm) during a 24-hour period, comparing SH-AID and DH-AID among pwT1D. Data from meals of each participant was pooled. Primary outcome was time in range % (TIR%, 70 to 180 mg/dL), calculated by continuous glucose monitoring during the 4-hour postprandial period. Paired t-test was used to compare the two groups. Results: Eighteen adult participants were included (mean age [SD] 43 [14] years, mean duration of T1D 20 [11] years, mean HbA1c 7.6% [1.0], mean daily insulin intake 26.70 [11.04] units). Postprandial TIR% was similar between SH and DH-AID (66.4% vs 70.2%, p=0.443). Less time in postprandial hypoglycemia (<70 mg/dL) was observed in the DH-AID group compared to SH-AID (5.4% vs 11.9%, p=0.019). No difference was observed in postprandial time spent in hyperglycemia (>180 mg/dL), glycemic variability indices or insulin intake between the two groups. Conclusion: Compared with SH-AID, DH-AID reduces postprandial hypoglycemia, while other postprandial glucose metrics remain similar among adult pwT1D. Disclosure M. Lebbar: None. J. Molveau: None. V. Boudreau: None. R. Rabasa-lhoret: Consultant; Dexcom, Inc., Abbott, Janssen Pharmaceuticals, Inc., Novo Nordisk Canada Inc., Sanofi, Lilly, Tandem Diabetes Care, Inc., Insulet Corporation. Z. Wu: Other Relationship; Eli Lilly and Company.
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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 | 0.001 | 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".