Effects of resistance training on resting blood pressure in hypertensive population: a systematic review of randomized controlled trials
Bibliographic record
Abstract
Background: The number of people with arterial hypertension is rising every year.Regular resistance training (RT) plays a significant role in blood pressure (BP) management because it can improve hypertension-related factors.Previous reviews relating to the effectiveness of exercise for hypertension showed positive results in the normalization of BP.However, they had a wide range of populations and mixed exercise interventions.Aims: The purpose of this paper was to systematically review the current literature examining the effects of RT on resting BP in people with hypertension compared to the control group (CG). Material and methods:The systematic review was carried out following the PRISMA statement between November and December 2022.After searching PubMed, Cochrane Library, and PEDro databases, reviewing potential studies in detail, and checking whether they met the eligibility criteria, nine studies were used in the review.The PEDro scale was used to establish the quality of included studies.Mean difference and Effect Size dppc2 were chosen to estimate the magnitude of RT effects.Results: Regarding systolic blood pressure (SBP), eight studies showed positive results in RT favor, and 1 showed positive results in CG favor.The average value for the mean difference was 10 mmHg.Regarding diastolic blood pressure (DBP), seven Studies showed positive results in RT favor, 1 showed positive results in CG favor, and 1 showed no difference.The average value for the mean difference was 4.6 mmHg.Conclusions: This work showed that RT has a good chance of improving resting BP values in the hypertensive population.However, more good quality studies supported by statistical analysis are needed to draw firm inferences.Due to the limitations of this review, no firm conclusions cannot be drawn.
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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 | 0.020 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".