724-P: Timing of Basal Insulin Reduction to Prevent Hypoglycemia during Exercise in Adults and Adolescents with Type 1 Diabetes Using Insulin Pump Therapy: Preliminary Results
Bibliographic record
Abstract
Background We have shown that the reduction of basal insulin (-80%) 40-min before exercise is insufficient to reduce the time spent on hypoglycemia (Roy-Fleming et al., 2018. Diabetes and Metabolism). These results suggest that earlier basal insulin reductions need to be tested. We compared the efficacy of two timings to decrease basal insulin infusion rate to reduce exercise-induced hypoglycemia in patients with T1D using insulin pump therapy. Furthermore, we explored if decreased muscle vasoreactivity (secondary to decreased insulin levels) is associated with a reduced time spent in hypoglycemia. Methods: 13 adults and adolescents (10 adults; 5 adolescents; mean A1C: 8,2±1,0%) practiced 60-min exercise sessions (ergocyle) at 60% VO2peak, 240 minutes after a standardized lunch. In randomized order, we compared an 80% reduction of basal insulin applied 40-min (T-40) and 90-min (T-90) before exercise onset. Near-infrared spectroscopy (NIRS) was used to investigate muscle hemodynamic at vastus lateralis. Venous blood samples for glycemia measurement were drawn every 10 min during exercise. Results: T-90 strategy could reduce hypoglycemia risk during exercise: glycemic drop during exercise tend to be more important during T-40 vs. T-90 strategy (-41.44 ± 57.65 mg/dl vs. -14.05 ± 34.23 mg/dl respectively; p=0.09). This trend is confirmed by the repeated measures ANOVA test, which shows a significant interaction effects (blood glucose level during exercise × strategy “T90 vs. T-40”) (p = 0.01). However, contrary to our hypothesis, the estimation of local muscle perfusion measured by NIRS shows comparable results between 2-strategies. Conclusion: Our preliminary results in 15 DT1 patients (planned 20) show that decreasing basal insulin infusion rate by 80% up to 90 minutes before exercise onset tend to reduce exercise-induced hypoglycemia. This drop does not seem to be related to a decrease in local muscle perfusion. Disclosure S. Tagougui: None. N. Taleb: None. E. Heyman: None. V. Messier: Other Relationship; Self; Eli Lilly and Company. C. Suppere: None. S. Berthoin: None. R. Rabasa-Lhoret: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Merck & Co., Inc., Novo Nordisk A/S, Sanofi. Research Support; Self; AstraZeneca, Janssen Pharmaceuticals, Inc., Novo Nordisk A/S.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".