Post‐exertional blood pressure response following swim exercise is dependent on training status
Bibliographic record
Abstract
Aerobic exercise is known to elicit a post‐exercise hypotensive (PEH) blood pressure (BP) response in both untrained and endurance‐trained subjects. However, it is not known if swim exercise produces a similar effect. We tested the hypothesis that an acute bout of swimming would fail to elicit a PEH response compared to an equivalent bout of stationary cycling, regardless of training state. 11 untrained and 10 trained healthy normotensive (systolic BP (SBP)/diastolic BP (DBP) < 120/80 mmHg) men and women (age 23 ± 1) underwent 30 min of intensity‐matched cycling and swimming exercise to assess changes in BP during a 75 min seated recovery. Cardiac output, stroke volume, total peripheral resistance, heart rate (HR), and heart rate variability (HRV) were also assessed. In untrained subjects, PEH was similar between cycling (−3.1±1 mmHg) and swimming (−5.8±1 mmHg). Trained individuals did not exhibit a PEH response following swimming (0.3±1 mmHg), yet had a significant drop in SBP at 50 min post cycling (−3.7±1 mmHg) (P < 0.05). The absence of PEH after swimming may reflect slower vagal reactivation (high frequency spectral component of HRV) (25 and 50 min) (P < 0.05), consistent with a significant increase in HR between modalities (P < 0.05). These results suggest that training may limit the potential for an effective PEH response to aerobic swimming. Funding was provided by the University of Toronto.
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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".