Leg blood flow and cardiac output are cyclically reduced during low‐intensity exercise with intermittent <scp>KAATSU</scp> cuff inflation in young adults
Bibliographic record
Abstract
) with bilateral KAATSU cuffs applied to the proximal thigh (KAATSU) or work-rate matched control exercise (CTL). During KAATSU trials, the cuffs were set to Cycle Mode (repeated 30-s inflation; 5-s deflation) at progressively increasing cuff pressure (150-220 mmHg). Right leg blood flow (LBF; Doppler and echo ultrasound) and cardiac output (CO; finger photoplethysmography) were measured continuously. The deflated KAATSU cuffs impaired exercising LBF (p < 0.01), with no further impairment during the first cuff inflation (p > 0.99). Following the initial cuff inflation, deflated KAATSU cuffs no longer compromised LBF (p = 0.78). Subsequently, LBF (p < 0.01) and CO (p = 0.04) were compromised during each of the remaining cuff inflations, but the magnitude of compromise was not augmented by progressive increases in cuff pressure (2LBF interaction: p = 0.41; CO interaction: p = 0.40). KAATSU cuff inflation reduces exercising LBF to a similar extent across cuff pressures. Furthermore, reductions in exercising CO during cuff inflation were immediately restored upon deflation, revealing the dependency of CO on exercising leg perfusion and subsequent venous return.
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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) | 0.000 | 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".