Exercise training improves blood pressure reactivity to stress: a systematic review and meta-analysis
Bibliographic record
Abstract
Blood pressure (BP) reactivity to stress is associated with cardiovascular events and the incidence of hypertension, therefore, tolerance to stressors is important for better management of cardiovascular risks. Exercise training is among the strategies that have been investigated as blunting the peak response to stressors, however, its efficacy is poorly explored. The aim was to explore the effects of exercise training (at least four weeks) on BP responses to stressor tasks in adults. A systematic review was performed in five electronic databases (MEDLINE, LILACS, EMBASE, SPORTDiscus, and PsycInfo). Twenty-three studies and one conference abstract was included in the qualitative analysis, totaling 1121 individuals, and k = 17 and 695 individuals in the meta-analysis. Favorable results (random-effects) for exercise training were found, with attenuated peak responses in systolic (standardized mean difference (SMD) = -0.34 [-0.56; -0.11], representing average reductions of 2.5 ± 3.6 mmHg) and null effects on diastolic BP (SMD = -0.20 [-0.54; 0.14], representing average reductions of 2.0 ± 3.5 mmHg). The analysis removing outliers' studies improved the effects for diastolic (SMD = -0.21 [-0.38; -0.05]) but not systolic BP (SMD = -0.33 [-0.53; -0.13]). In conclusion, exercise training seems to lower stress-related BP reactivity, therefore has the potential to improve patients' ability to better respond to stressful situations.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.029 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".