BLOOD PRESSURE RESPONSES TO STRESS AFTER CHRONIC PHYSICAL EXERCISE: A SYSTEMATIC REVIEW WITH META-ANALYSIS
Bibliographic record
Abstract
Objective: To assess the effects of physical exercise interventions on blood pressure (BP) responsiveness to laboratory stress tests. Design and method: This is a systematic review with meta-analysis that examined the effect of at least 4 weeks of exercise training on adults BP responsiveness to stressor tasks. For quantitative analysis, a random-effects model by Hunter Smith method was used. The searches were performed in 4 digital databases (PUBMED, LILACS, EMBASE and PsycInfo) and 19 studies and 2 event abstracts were included, totaling 857 individuals (12 studies and 516 individuals, in the quantitative phase). Results: Regarding qualitative analyses, 66.7% of the full text and abstracts showed favorable BP responses (either in SBP, DPB and/or MBP) after chronic exercise training, and the most frequent stressor test was the Arithmetic task, used in 33.3% of studies. Besides that, no asymmetries were found in the funnel graphs that would infer publication bias. Favorable metanalytic results for the exercises were found in systolic BP (SBP; mean effect size = -0.47 [-0.69; -0.24]) and diastolic BP (DBP; mean effect size = -0.35 [-0.58; -0.12). Conclusions: In summary, chronic physical exercise lowers SBP and DBP responsiveness to laboratory stress tests. So, these results associated with information from previous studies reinforce the idea that physical exercise is a valid strategy to control not only BP at rest but also its levels under stress, reducing hypertensive peaks of these individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.032 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".