275-OR: Change in Hypoglycemia Fear and Frequency with the Use of Automated Insulin Delivery—A Prospective Analysis of the Type 1 Diabetes Better Registry
Bibliographic record
Abstract
Introduction and Objective: Automated insulin delivery (AID) is expected to reduce the burden of hypoglycemia including fear of hypoglycemia (FOH) in type 1 diabetes (T1D). This study aimed to evaluate the change in hypoglycemia fear survey-II (HFS-II) scores and hypoglycemia frequency after AID initiation in usual-living conditions. Methods: Adults (≥18years) living with T1D from the Canadian Type1BETTER registry who started using an AID system during the follow-up period were included. Data included demographics, diabetes specific variables, and the validated HFS-II. Data were collected annually for three years. Results: A total of 115 participants (mean age 42.1±14.5 years; T1D duration 24.4±13.9 years; 77% identified as women) were included. At baseline, 49% of participants reported HbA1c ≤7.0%, which increased to 63% after AID initiation (p=0.047). Participants reported fewer hypoglycemia episodes over the previous month after starting AID compared to baseline. Specifically, the number of monthly level 2 hypoglycemia episodes (<3.0mmol/L with autonomous treatment) decreased from 6.0±7.0 to 4.1±4.5, p=0.022 and symptomatic nocturnal hypoglycemia decreased from 2.3±4.1 episodes to 1.6±2.6, p=0.012. Similarly, average HFS-II scores decreased after using AID: total from 34.0±17.6 at baseline to 30.0±19.4 (p=0.006), HFS-II Behavior subscale 15.9±7.5 to 14.0±8.0 (p=0.012), and HFS-II Worry subscale 18.2±13.3 to 15.9±13.4 (p=0.027). Conclusion: AID initiation was associated with improved HbA1c, reduced hypoglycemia frequency, and lowered HFS-II scores in adults with T1D in usual-living conditions. These findings support the potential of AID to reduce the burden of hypoglycemia without compromising overall glycemic management. Disclosure M.K. Talbo: Other Relationship; Dexcom, Inc. T. Peters: None. C. South: None. A. Katz: None. J. Yale: Advisory Panel; Eli Lilly and Company. Speaker's Bureau; Eli Lilly and Company. Advisory Panel; Novo Nordisk. Speaker's Bureau; Novo Nordisk. Advisory Panel; Abbott. Speaker's Bureau; Abbott, GlaxoSmithKline plc. Advisory Panel; Sanofi. Speaker's Bureau; Bayer Pharmaceuticals, Inc, Dexcom, Inc. Advisory Panel; Dexcom, Inc., Ypsomed AG, Bayer Pharmaceuticals, Inc. Speaker's Bureau; Insulet Corporation. R.P. Rabasa-Lhoret: Advisory Panel; Abbott, Eli Lilly and Company, Novo Nordisk, Sanofi, Insulet Corporation. Other Relationship; Medtronic. Advisory Panel; Bayer Pharmaceuticals, Inc. A. Brazeau: Speaker's Bureau; Dexcom, Inc. Research Support; Canadian Institutes of Health Research. Speaker's Bureau; Juvenile Diabetes Research Foundation (JDRF). Research Support; Juvenile Diabetes Research Foundation (JDRF), Diabète Québec, Fonds de recherches du Québec-Santé, Mitacs.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".