A Comparison of Glucose and Additional Signals for Three Different Exercise Types in Adolescents with Type 1 Diabetes Using a Hybrid Closed-Loop System
Bibliographic record
Abstract
Objective: To compare glycemic outcomes during and following moderate-intensity exercise (MIE), high-intensity interval exercise (HIE), and resistance exercise (RE) in adolescents with type 1 diabetes (T1D) using a hybrid closed-loop (HCL) insulin pump while measuring additional physiological signals associated with activity. Methods: Twenty-eight adolescents (average age 16.3 ± 2.1 years, 50% females, average duration of T1D 9.4 ± 4 years) using HCL (Medtronic MiniMed 670G) undertook 40 min of MIE, HIE, and RE. A temporary glucose target (8.3 mmol/L, 150 mg/dL) was set for 2 h prior and during exercise. Heart rate, accelerometer, venous glucose, lactate, ketones, and counter-regulatory hormones were measured for 280 min postexercise commencement. The primary outcome was glucose percentage time in range (TIR): 3.9–10 mmol/L (70–180 mg/dL) for 14 h from exercise onset. Results: Median (interquartile range) TIR for HIE was 88 (78, 96)%, MIE 79 (63, 88)%, and RE 86 (72, 95)% for 14 h from exercise onset. For MIE compared with HIE, TIR was lower ( P = 0.012) and time above range (TAR) was greater (18 [2.4, 28] vs. 6.9 [0.0, 14]%, P = 0.041). Hypoglycemia occurred in 13 (46%), 11 (39%), and 14 (50%) of participants for HIE, MIE, and RE, respectively, the majority following the meal after exercise. There were higher levels of lactate ( P = 0.001), growth hormone ( P = 0.001), noradrenaline ( P = 0.001), and heart rate ( P = 0.01) during HIE and RE compared with MIE. Conclusions : HCL use in adolescents with T1D results in excellent TIR during different forms of exercise when a temporary target is set 2 h before. Extending the temporary target after exercise may also be needed to help minimize postexercise hypoglycemia.
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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) | 0.000 | 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 | 0.000 |
| 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".