Short-Term High-Intensity Interval Training Reduces Hyperglycemia in Type 2 Diabetics
Bibliographic record
Abstract
Glycemic regulation is impaired in individuals with type 2 diabetes (T2D). Current guidelines recommend that people with T2D should participate in a cumulative total of 150 minutes of continuous, moderate-intensity aerobic exercise each week, or at least 90 minutes of vigorous intensity exercise. While effective for improving glycemic control, most individuals with T2D do not perform sufficient activity to achieve health benefits, often citing "lack of time" as a key barrier to regular exercise participation. Low-volume high-intensity interval training (HIT) is a potent stimulus for inducing metabolic adaptations typically associated with traditional high-volume endurance training. However, the effects of low-volume HIT on glycemic control in people with T2D is currently unknown. PURPOSE: To determine the utility of HIT to reduce hyperglycemia in patients with T2D in a practical, time-efficient manner. METHODS: 7 subjects with T2D (age: 62 ± 3 yr, BMI: 33 ± 3.8 kg/m2, Wmax: 125 ± 18 W) performed 6 training sessions over 2 wk. Each session consisted of 10 × 1 min cycling efforts at ∼90% Wmax elicited during a ramp VO2peak test, interspersed with 1 min of rest (113 ± 11 W). Continuous Glucose Monitoring (CGM) technology (Medtronic CGMS® iPro Recorder) was employed under standard dietary conditions for a 24 hr period on a pre-training control day and ∼48-72 hr following the final training session. RESULTS: CGM data revealed lower mean 24 hr blood glucose concentration following HIT (7.6 ± 0.5 mmol/L vs. 6.6 ± 0.3 mmol/L, p < 0.05). The sum of the 3 hr postprandial area under the glucose curve for breakfast, lunch and dinner was also reduced following training (689 ± 196 mmol/L × 9hr vs. 991 ± 214 mmol/L × 9hr, p < 0.05). CONCLUSIONS: These preliminary data shed light on the potential for low-volume HIT to represent a unique, time-efficient exercise strategy to improve glycemic regulation in people with T2D. Supported by the Canadian Diabetes Association
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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 | 0.000 |
| 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".