Impact of β-blocker treatment and nutritional status on glycemic response during exercise in patients with type 2 diabetes
Bibliographic record
Abstract
PURPOSE: Most individuals with type 2 diabetes are affected by hypertension and thus have higher risk of cardiac complications. In addition to behavioural modifications, such as healthy food choices and regular physical activity, beta-blocker treatment may be considered to reduce morbidity and mortality, especially after a cardiovascular event. However, this medication is generally associated with a deleterious impact on glucose metabolism. The objective of the study was to assess the impact of beta-blocker treatment on glucose response during exercise in patients with type 2 diabetes, free of cardiovascular complications. METHODS: Ten sedentary men, treated with diet and/or hypoglycemic agents have performed four exercise sessions at 60% of their V O2peak, in the fasted state or 2 hours following a standardized breakfast, with and without beta-blockers (atenolol 100 mg id for five consecutive days). Blood samples were drawn during the resting period, at 15-min intervals during the exercise session and during the recovery period. RESULTS: A reduction of blood glucose levels was observed following the exercise session in the postprandial state (48% and 44% reduction with and without beta-blockers respectively; P < 0.001). One hour of exercise performed in the fasted state had a minimal impact on glucose and insulin levels, whether with or without beta-blockers. beta-blocker treatment was not associated with increased baseline blood glucose or insulin levels in the fasted or the postprandial situation. CONCLUSION: Dietary status has a more important impact on plasma glucose and insulin modulation than short-term use of beta-blockers.
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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) | 0.001 | 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".