274-OR: Do-It-Yourself Automated Insulin Delivery (AID) Systems Are Noninferior to Commercial AID Systems in Glucose Management among Adults with Type 1 Diabetes
Bibliographic record
Abstract
AIM: We aim to compare commercial automated insulin delivery (C-AID) systems with open-source do-it-yourself (DIY)-AID systems for glucose management among adults with type 1 diabetes (T1D) in real-life conditions. METHODS: A prospective observational, non-inferiority, parallel-cohort study involving 77 adults with T1D, having used an AID for ≥3 months and living in Canada (25 DIY-AID and 52 C-AID users): 59.7% females, mean age 44.0 ± 14.7 years old with mean diabetes duration of 26.9 ± 14.5 years and HbA1c of 6.7 ± 0.7%. A total of 30 days’ data from an additional blinded CGM (Dexcom G6) was used to assess effectiveness [Primary outcome: 24h time in range% (TIR%) for 30 days]. RESULTS: DIY-AIDs were non-inferior to C-AIDs regarding the TIR% [78.3±11.0% vs. 71.2±10.9%, mean difference 7.2% [95% CI 1.9% to 12.5%], P<0.001 for non-inferiority (non-inferiority margin 5%)], even after adjusting for various confounding factors (age, sex, auto-mode%, duration of AID use, annual household income, and educational level). The percentage of time in hypoglycemia (<70 mg/dL) was higher with DIY-AID (3.9±3.1%) than with C-AID (1.8±1.3%) but still below recommended threshold (Table). Differences between both systems are more pronounced during daytime. CONCLUSION: DIY-AIDs are non-inferior to C-AIDs for TIR% among adults with T1D in real-world settings. Disclosure Z.Wu: Other Relationship; Eli Lilly and Company. R.Rabasa-lhoret: Consultant; Dexcom, Inc., Abbott, Janssen Pharmaceuticals, Inc., Novo Nordisk Canada Inc., Sanofi, Lilly, Tandem Diabetes Care, Inc., Insulet Corporation. M.Lebbar: None. A.Bonhoure: Consultant; Dexcom, Inc. M.Raffray: None. M.Devaux: None. C.Grou: None. V.Messier: None. V.Boudreau: None. A.Brazeau: Other Relationship; Dexcom, Inc., Diabète québec, Ordre des diététistes nutritionnistes du Québec, Research Support; Canadian Institutes of Health Research, Fonds de recherche du Québec en Santé. Funding Canadian Institutes of Health Research (148464)
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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 | 0.005 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".