955-P: A Prospective Analysis of the Canadian Patient Transition Experience to Two Advanced Hybrid Closed-Loop Insulin Pump Technologies
Bibliographic record
Abstract
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.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".