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Record W4411293210 · doi:10.2337/db25-955-p

955-P: A Prospective Analysis of the Canadian Patient Transition Experience to Two Advanced Hybrid Closed-Loop Insulin Pump Technologies

2025· article· en· W4411293210 on OpenAlexaboutno aff
GURLEEN NIRWAL, SAHARA FROJMOVIC, ASHINI DISSANAYAKE, Jessica MacKenzie-Feder, Benjamin Schroeder, Adam White, Monika Pawłowska

Bibliographic record

VenueDiabetes · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsnot available
Fundersnot available
KeywordsInsulin pumpClosed loopInsulinLoop (graph theory)MedicineTransition (genetics)Internal medicineEndocrinologyDiabetes mellitusType 1 diabetesEngineeringChemistryMathematicsControl engineeringBiochemistry

Abstract

fetched live from OpenAlex

Introduction and Objective: Advanced hybrid closed-loop (AHCL) insulin pump therapy is a significant development in diabetes treatment. We assessed the real-world experience of patients transitioning to two Health Canada-approved AHCL insulin pumps and their effect on diabetes distress. Methods: We evaluated 48 adults with T1D shifting from multiple daily injection, standard pump or hybrid closed loop pump therapy to one of two AHCL systems: Tandem t:slim X2 with Control IQ™ (n=31) or Medtronic MiniMed 780G with SmartGuard™ (n=17). Diabetes distress (measured by the T1-DDS) and HbA1c at baseline and 6 months post-transition were compared using a paired t-test. Participant comfort, trust and satisfaction with AHCL were assessed with 5-point Likert scale questions, free-text surveys and interviews. Results: After 6 months on AHCL, participants (52% female, mean age 46.0 ± 4.1 yrs) exhibited significant diabetes distress reductions in powerlessness (-0.60 ± 0.30, p<0.001), management (-0.71 ± 0.22, p<0.0000001), hypoglycemia (-0.42 ± 0.31, p=0.01), eating (-0.65 ± 0.29, p<0.00001) and total distress (-0.60 ± 0.21, p<0.000001). Moreover, HbA1c was significantly reduced (-0.55 ± 0.20%, p<0.00001). Most participants (87%) did not find AHCL to be too complicated, with 70% noting a reduced workload. Some (23%) participants reported that AHCL was difficult to trust, but 77% felt that their trust improved over time. Most participants (62%) had no challenges transitioning to AHCL. In total, 90% of participants were satisfied with AHCL and would recommend it to others, while 85% felt that AHCL met their expectations. Emerging qualitative themes were increased freedom in eating, fewer lows at night, lower workload and improved glycemic control. Areas for improvement included sensor reliability, sensor longevity and recurrent alarms. Conclusion: Overall, participants benefited from increased glycemic control and decreased diabetes distress with AHCL. Disclosure G. Nirwal: None. J. Adams: None. S. Frojmovic: None. T. Chang: None. A. Dissanayake: None. J. MacKenzie-Feder: Advisory Panel; Pfizer Inc, Recordati. B. Schroeder: None. A. White: Speaker's Bureau; Boehringer-Ingelheim. Advisory Panel; Eli Lilly and Company. Other Relationship; Medtronic. Advisory Panel; Novo Nordisk. M. Pawlowska: Advisory Panel; Medtronic, Amgen Inc.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.162

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.001
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 head0.007
GPT teacher head0.275
Teacher spread0.267 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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