Twelve Weeks of Sprint Interval Training Improves Indices of Cardiometabolic Health Similar to Traditional Endurance Training despite a Five-Fold Lower Exercise Volume and Time Commitment
Bibliographic record
Abstract
AIMS: We investigated whether sprint interval training (SIT) was a time-efficient exercise strategy to improve insulin sensitivity and other indices of cardiometabolic health to the same extent as traditional moderate-intensity continuous training (MICT). SIT involved 1 minute of intense exercise within a 10-minute time commitment, whereas MICT involved 50 minutes of continuous exercise per session. METHODS: Sedentary men (27±8y; BMI = 26±6kg/m2) performed three weekly sessions of SIT (n = 9) or MICT (n = 10) for 12 weeks or served as non-training controls (n = 6). SIT involved 3x20-second 'all-out' cycle sprints (~500W) interspersed with 2 minutes of cycling at 50W, whereas MICT involved 45 minutes of continuous cycling at ~70% maximal heart rate (~110W). Both protocols involved a 2-minute warm-up and 3-minute cool-down at 50W. RESULTS: Peak oxygen uptake increased after training by 19% in both groups (SIT: 32±7 to 38±8; MICT: 34±6 to 40±8ml/kg/min; p<0.001 for both). Insulin sensitivity index (CSI), determined by intravenous glucose tolerance tests performed before and 72 hours after training, increased similarly after SIT (4.9±2.5 to 7.5±4.7, p = 0.002) and MICT (5.0±3.3 to 6.7±5.0 x 10-4 min-1 [μU/mL]-1, p = 0.013) (p<0.05). Skeletal muscle mitochondrial content also increased similarly after SIT and MICT, as primarily reflected by the maximal activity of citrate synthase (CS; P<0.001). The corresponding changes in the control group were small for VO2peak (p = 0.99), CSI (p = 0.63) and CS (p = 0.97). CONCLUSIONS: Twelve weeks of brief intense interval exercise improved indices of cardiometabolic health to the same extent as traditional endurance training in sedentary men, despite a five-fold lower exercise volume and time commitment.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".