Prescribing high-intensity interval exercise by RPE in individuals with type 2 diabetes: metabolic and hemodynamic responses
Bibliographic record
Abstract
We tested the hypothesis that rating of perceived exertion (RPE) is a tool as efficient as the heart rate (HR) response to the cardiopulmonary exercise test (CPX) for prescribing and self-regulating high-intensity interval exercise (HIIE), and that metabolic and hemodynamic response to HIIE is superior than to continuous moderate-intensity exercise (MICE) in individuals with type 2 diabetes mellitus (T2DM). Eleven participants (age = 52.3 ± 3 years) underwent HIIE prescribed and self-regulated by RPE (HIIERPE; 25 min), HIIE prescribed and regulated by an individual’s HR response to CPX (HIIEHR; 25 min), MICE prescribed and self-regulated by RPE (30 min) and control (30 min of seated resting) intervention in random order. HR, blood pressure (BP), capillary glucose, endothelial reactivity, and carotid-femoral pulse wave velocity were assessed before, immediately after, and 45 min after each intervention. Exercise HR, speed, and distance were measured during exercise sessions. Twenty-four-hour ambulatory BP was measured after each intervention. Exercise HR, speed, and distance were similar between HIIERPE and HIIEHR. BP response was not different among HIIERPE, HIIEHR, and MICE. Capillary glycaemia reduction was greater (P < 0.05) after HIIERPE (48.6 ± 9.6 mg/dL) and HIIEHR (47.2 ± 9.5 mg/dL) than MICE (29.5 ± 11.5 mg/dL). Reduction (P < 0.05) in 24-h (6.7 ± 2.2 mm Hg) and tendency toward reduction (P = 0.06) in daytime systolic (7.0 ± 2.5 mm Hg) ambulatory BP were found only after HIIERPE. These results suggest that HIIE is superior to MICE for reducing glycaemia and ambulatory BP, and that the 6–20 RPE scale is a useful tool for prescribing and self-regulating HIIE in individuals with T2DM.
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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) | 0.000 | 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".