Improved Open-Loop Glucose Control With Basal Insulin Reduction 90 Minutes Before Aerobic Exercise in Patients With Type 1 Diabetes on Continuous Subcutaneous Insulin Infusion
Bibliographic record
Abstract
OBJECTIVE To reduce exercise-associated hypoglycemia, individuals with type 1 diabetes on continuous subcutaneous insulin infusion typically perform basal rate reductions (BRRs) and/or carbohydrate feeding, although the timing and amount of BRRs necessary to prevent hypoglycemia are unclear. The goal of this study was to determine if BRRs set 90 min pre-exercise better attenuate hypoglycemia versus pump suspension (PS) at exercise onset. RESEARCH DESIGN AND METHODS Seventeen individuals completed three 60-min treadmill exercise (∼50% of VO2peak) visits in a randomized crossover design. The insulin strategies included 1) PS at exercise onset, 2) 80% BRR set 90 min pre-exercise, and 3) 50% BRR set 90 min pre-exercise. RESULTS Blood glucose level at exercise onset was higher with 50% BRR (191 ± 49 mg/dL) vs. 80% BRR (164 ± 41 mg/dL; P < 0.001) and PS (164 ± 45 mg/dL; P < 0.001). By exercise end, 80% BRR showed the smallest drop (−31 ± 58 mg/dL) vs. 50% BRR (−47 ± 50 mg/dL; P = 0.04) and PS (−67 ± 41 mg/dL; P < 0.001). With PS, 7 out of 17 participants developed hypoglycemia versus 1 out of 17 in both BRR conditions (P < 0.05). Following a standardized meal postexercise, glucose rose with PS and 50% BRR (both P < 0.05), but failed to rise with 80% BRR (P = 0.16). Based on interstitial glucose, overnight mean percent time in range was 83%, 83%, and 78%, and time in hypoglycemia was 2%, 1%, and 5% with 80% BRR, 50% BRR, and PS, respectively (all P > 0.05). CONCLUSIONS Overall, a 50–80% BRR set 90 min pre-exercise improves glucose control and decreases hypoglycemia risk during exercise better than PS at exercise onset, while not compromising the postexercise meal glucose control.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.001 | 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".