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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".