Very-low-load resistance exercise in the upper body with and without blood flow restriction: cardiovascular outcomes
Bibliographic record
Abstract
It is proposed that, at very low loads, greater blood flow restriction (BFR) pressures might be required for muscular adaptation to occur. The cardiovascular and hyperemic response to very low loads combined with relative levels of BFR is unknown. Ninety-seven participants were recruited and assigned to 1 of 4 exercise conditions: 15% of 1-repetition maximum (1RM) without BFR (15/00), 15% 1RM with BFR at 40% of arterial occlusion pressure (AOP) (15/40), 15% of 1RM with BFR at 80% of AOP (15/80), and 70% of 1RM without BFR (70/00). Participants performed 4 sets of unilateral biceps curls. Blood pressure was measured before and after exercise; brachial artery blood flow was measured before exercise, following the second set, and 1 min following exercise. Systolic blood pressure increased following exercise in all conditions (+10 (11) mm Hg, P < 0.0005). Diastolic pressure increased in all but 70/00 (+2 (11) mm Hg, P = 0.107). Brachial artery blood flow increased following the second set of exercise in all but 15/80 (+43.4 (76.8) mL·min−1, P = 0.348). One minute following exercise and cuff deflation, there were no differences in blood flow between conditions (P > 0.05). Similarly, artery diameter was increased in all conditions except 15/80 (+0.002 (0.041) cm, P = 0.853) following the second set, and increased in all conditions by 1 min following exercise (P < 0.05). In conclusion, exercise-induced hyperemia is blunted with increasing pressures of BFR. There is a modest increase in blood pressure at very low loads of resistance exercise in the upper body.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".