Continuous moderate and intermittent high-intensity exercise in youth with type 1 diabetes: Which protection for dysglycemia?
Bibliographic record
Abstract
Aim From an early age, exercise is key to managing type 1 diabetes (T1D). However, hypoglycemia around aerobic exercise is a major barrier to physical activity in children. We explore whether intermittent high-intensity aerobic exercise (IHE), designed to mimic spontaneous childhood physical activity patterns, offers better protection against glycemic drop than continuous moderate-intensity exercise (CME). Methods Five boys and 7 girls with T1D (9.8 ± 1.4y) performed ergo cycle-based randomized CME and IHE of identical duration and total mechanical load [50 %PWC 170 vs. 15sec(150 %PWC 170 )/30 sec passive recovery; both during two 10-min sets, 5 min in-between]. Capillary glycemia during exercise and interstitial glucose during recovery were compared between exercises and an inactive condition, controlling for baseline glycemia, carbohydrate and insulin. Results The exercise-induced decrease in capillary glycemia was attenuated by 1.47 mmol·L −1 for IHE vs . CME ( P < 0.05). No symptomatic hypoglycemic episodes occurred during exercises. Post-exercise time in hypoglycemia did not differ between conditions. During early recovery, CME reduced time spent > 16.7 mmol·L −1 compared with inactive days ( P < 0.05; CME: 0 %; IHE: 16,7 %; INACTIVE: 41,7 %). Conclusion IHE appeared to limit the glycemic drop compared to CME. Performing 20-min CME or IHE was not associated with increased hypoglycemic risk compared to being inactive. CME appeared even transiently protective against serious hyperglycemia.
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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 | 0.000 |
| 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".