2084-LB: A Randomized Multicenter Trial of Hybrid Closed-Loop Insulin Therapy with Control-IQ Technology in Type 1 Diabetes in Pregnancy
Bibliographic record
Abstract
Introduction and Objective: The efficacy of hybrid closed-loop insulin therapy (HCL) in pregnancy varies by system. Our objective was to assess the efficacy in pregnancy of a HCL that is in common use outside of pregnancy. Methods: This multicenter, open-label trial randomized pregnant women with type 1 diabetes (T1D) and early pregnancy A1C of 6.2-10%, at 14 sites in Canada and Australia, to start HCL (t:slim X2 insulin pump with Control-IQ technology with Dexcom G6 sensor) by 16 weeks gestation or continue with standard care with continuous glucose monitoring (CGM). Use of the lowest target range (sleep activity) was recommended throughout the day and night with the optional use of the highest target range for exercise. The primary outcome was the percentage of time that glucose was in the pregnancy range of 63 to 140mg/dL [3.5 to 7.8mmol/L] (TIRp) as measured by CGM from 16 to 34weeks +6days gestation adjusted for site, baseline TIRp and baseline mode of insulin delivery, using intention-to-treat principles. Secondary outcomes included time above 140mg/dL (7.8mmol/L), time below 63mg/dL (3.5mmol/L), mean glucose, safety events and pregnancy outcomes. Results: A total of 91 women (mean ± SD: age 31.7 ± 5.2 years, diabetes duration 19.0 ± 8.1 years, early pregnancy A1C 7.4 ± 1.0%) were randomized (46 to HCL and 45 to standard care). The mean adjusted TIRp was 12.6 percentage points (95% CI 9.9,15.2; p<0.001) higher in HCL than standard care (65.4 ± 9.5% versus 50.3 ± 13.9%, respectively) with 11.4 percentage points less time above range (95% CI 8.6,14.2 p<0.001) and 1.04 percentage points less time below 63mg/dL (95%CI 0.6,1.48 p<0.001). The adjusted mean glucose was 11.2mg/dL (0.62 mmol/L) lower with HCL versus standard care (95%CI 7.2,16.2 p<0.001). There was 1 episode of severe hypoglycemia with HCL and 0 with standard care and 2 episodes of diabetic ketoacidosis in each of the trial arms. Conclusion: This HCL resulted in 3 more hours/day spent in TIRp in T1D pregnancy compared to standard care. No safety concerns arose. Disclosure L.E. Donovan: Other Relationship; Medtronic, Dexcom, Inc., Tandem Diabetes Care, Inc, Inner Analytics. P. Lemieux: Advisory Panel; Dexcom, Inc. A. Dunlop: None. J.M. Yamamoto: Other Relationship; Abbott. H.R. Murphy: Research Support; Abbott, Dexcom, Inc. Advisory Panel; Medtronic, Ypsomed AG. Speaker's Bureau; Eli Lilly and Company, Dexcom, Inc., Ypsomed AG, Novo Nordisk, Sanofi. D. Simmons: Research Support; Novo Nordisk, AMSL. Other Relationship; Abbott, Abbott, Boehringer-Ingelheim. Speaker's Bureau; Ascensia Diabetes Care. R.C. Bell: None. K. Chaput: None. J.L. Benham: None. G.P. Ross: None. K. Nerenberg: None. K. Mohammad: None. B.A. Perkins: Other Relationship; Abbott, Novo Nordisk, Sanofi. Advisory Panel; Abbott, Insulet Corporation, Sanofi, Novo Nordisk, Nephris, Vertex Pharmaceuticals Incorporated. Research Support; Novo Nordisk. J.E. Booth: None. H.N. Ntanda: None. G. Tomlinson: None. D. Feig: Other Relationship; Novo Nordisk. Consultant; Ypsomed. Funding Diabetes Canada (OG-3-21-5570-LD); Australia Medical Research Future Fund (MRFF); lnternational Clinical Trial Collaboration (2022/MRF2023992)
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".