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Record W4281635632 · doi:10.2337/db22-762-p

762-P: Comparing Dual-Hormone and Single-Hormone Automated Insulin Delivery System on Nocturnal Glucose Management among Pediatric People Living with Type 1 Diabetes : A Pooled Analysis

2022· article· en· W4281635632 on OpenAlexaboutno aff
ZEKAI WU, Virginie Messier, Maha Lebbar, RÉMI RABASA-LHORET

Bibliographic record

VenueDiabetes · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGlycemicInsulinInsulin deliveryType 1 diabetesInternal medicineDiabetes mellitusPediatricsEndocrinology

Abstract

fetched live from OpenAlex

Background: Only three studies have directly compared the efficacy of dual-hormone (DH) automated insulin delivery (AID) systems and single-hormone (SH) AID on overnight glucose management in pediatric people living with type 1 diabetes (PPWT1D) . Their conclusions differ. Pooling data could lead to stronger conclusions. Methods: Pooled data from 3 open-label, randomized, controlled, crossover studies on comparing DH-AID and SH-AID among PPWT1D (8-17 y/o) . The primary outcome was time in range% (TIR%) overnight (00:00-06:00) based on continuous glucose monitoring. Paired t-test was applied to compare the two groups. Results: Records from 50 PPWT1D [median (Q1-Q3) age: 14.0 years (11.8, 16.0) , mean ± SD HbA1c: 8.2 ± 0.8%] provided 246 nights of data (Table) . TIR% [ (median (IQR) ] for SH-AID and DH-AID was 91.3% (58.3, 100.0) and 94.4% (76.4, 100.0) , respectively (P=0.024) . DH-AID was superior to SH-AID in reducing time in hypo- (<3.9 mmol/L) and hyperglycemia (>13.9 mmol/L) but not glycemic variability. Conclusion: DH-AID has the potential to provide better overnight glucose management than SH-AID in PPWT1D. Disclosure Z.Wu: Other Relationship; Eli Lilly and Company. V.Messier: None. M.Lebbar: None. R.Rabasa-lhoret: Consultant; HLS Therapeutics Inc., Pfizer Inc., Other Relationship; Abbott Diabetes, AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Janssen Pharmaceuticals, Inc., Medtronic, Merck & Co., Inc., Novo Nordisk Canada Inc., Sanofi, Vertex Pharmaceuticals Incorporated, Research Support; Canadian Institutes of Health Research, Cystic Fibrosis Canada, Diabetes Canada, Fondation Francophone pour la Recherche en Diabète (FFRD) , JDRF, National Institutes of Health, Société Francophone du Diabète (SFD) , Speaker's Bureau; Canadian Medical & Surgical Knowledge Translation Research Group (CMS) , CPD Network, Tandem Diabetes Care, Inc. Funding Diabetes Canada grant (OG-2-12-3868-RR,OG-2-13-42P, OG-3-14-4500-RR) and Fondation JA De Sève

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)0.019
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.023
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.010
GPT teacher head0.220
Teacher spread0.210 · 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 designMeta-analysis
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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