Late Afternoon Vigorous Exercise Increases Postmeal but Not Overnight Hypoglycemia in Adults with Type 1 Diabetes Managed with Automated Insulin Delivery
Bibliographic record
Abstract
Aim: To compare evening and overnight hypoglycemia risk after late afternoon exercise with a nonexercise control day in adults with type 1 diabetes using automated insulin delivery (AID). Methods: Thirty adults with type 1 diabetes using AID (Minimed 670G) performed in random order 40 min high intensity interval aerobic exercise (HIE), resistance (RE), and moderate intensity aerobic exercise (MIE) exercise each separated by >1 week. The closed-loop set-point was temporarily increased 2 h pre-exercise and a snack eaten if plasma glucose was ≤126 mg/dL pre-exercise. Exercise commenced at ∼16:00. A standardized meal was eaten at ∼20:40. Hypoglycemic events were defined as a continuous glucose monitor (CGM) reading <70 mg/dL for ≥15 min. Four-hour postevening meal and overnight (00:00–06:00) CGM metrics for exercise were compared with the prior nonexercise day. Results: There was no severe hypoglycemia. Between 00:00 and 06:00, the proportion of nights with hypoglycemia did not differ postexercise versus control for HIE (18% vs. 11%; P = 0.688), RE (4% vs. 14%; P = 0.375), and MIE (7% vs. 14%; P = 0.625). Time in range (TIR) (70–180 mg/dL), >75% for all nights, did not differ between exercise conditions and control. Hypoglycemia episodes postmeal after exercise versus control did not differ for HIE (22% vs. 7%; P = 0.219) and MIE (10% vs. 14%; P > 0.999), but were greater post-RE (39% vs. 10%; P = 0.012). Conclusions: Overnight TIR was excellent with AID without increased hypoglycemia postexercise between 00:00 and 06:00 compared with nonexercise days. In contrast, hypoglycemia risk was increased after the first meal post-RE, suggesting the importance of greater vigilance and specific guidelines for meal-time dosing, particularly with vigorous RE. ACTRN12618000905268
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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) | 0.000 | 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".