Effects of 8-Week Isometric Handgrip Training on Resting Arterial Pressure
Bibliographic record
Abstract
Hypertension (HTN) is the chronic elevation of resting blood pressure and is estimated to affect 30% of the global population. HTN is treated with lifestyle modifications and pharmacologic agents. Isometric handgrip training (IHG) has been shown to reduce resting blood pressure in normotensive and hypertensive individuals following training using programmable, digital handgrips. The purpose was to replicate previous IHG results with common spring handgrips. A randomized control trial of 49 normotensive participants (66.4±0.9 years) was conducted. Participants who were randomized to the exercise group (n=25) trained 3 times per week for 8 weeks. Control participants (n=24) completed weekly blood pressure measurements. Blood pressure was assessed during 3 pre and 3 post-training visits. Statistical analysis was completed using a two-way ANOVA. Following 8 weeks of IHG exercise trained participants demonstrated significant reductions in resting blood pressure and pulse pressure. Systolic and diastolic blood pressures were reduced from 122±3 mmHg to 112±3 mmHg (p<0.001) and 70±1 mmHg to 67±1 mmHg (p<0.05) respectively. Pulse pressure was reduced by 7 mmHg following IHG training (52±3 mmHg to 45±3 mmHg, p<0.05). Heart rate remained unaltered with training. No change in any measure over the study duration was observed for participants in the non-exercise control group. In agreement with previous studies, IHG reduced resting arterial pressure following 8 weeks of training. Specifically, readily available spring handgrips appear to be able to reproduce the results previously observed using programmable, digital handgrip devices. Supported by the National Sciences and Engineering Research Council of Canada Discovery Grant (NSERC).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".