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Record W4381377536 · doi:10.2337/db23-274-or

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

2023· article· en· W4381377536 on OpenAlexaboutno aff
ZEKAI WU, Maha Lebbar, Anne Bonhoure, Marie Raffray, MARIE DEVAUX, Caroline Grou, Virginie Messier, Valérie Boudreau, ANNE-SOPHIE BRAZEAU, RÉMI RABASA-LHORET

Bibliographic record

VenueDiabetes · 2023
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInsulin deliveryType 1 diabetesConfoundingHypoglycemiaObservational studyInsulinCohortDiabetes mellitusType 2 diabetesDemographyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

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)

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.019
GPT teacher head0.273
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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