Low-Intensity Resistance Exercise with Blood Flow Restriction Improves Balance in Elderly Women: A Comparative Study on the Lower Quarter Y-Balance Test
Bibliographic record
Abstract
Introduction: Enhancing leg muscle strength in elderly could play a crucial role in reducing fall risk. A novel approach to enhance muscular strength involves the use of low-intensity resistance exercises in conjunction with blood flow restriction (BFR), as an alternative to high-intensity exercise. This study aimed to evaluate the effects of low-intensity strength exercise with BFR on lower quarter Y-balance test (LQ-YBT) performance, compare to moderate-intensity strength exercise in elderly female.Methods: The study employed a true experimental randomized design, assessing balance using the LQ-YBT in 26 elderly women over a six-week exercise period. Subjects were divided into two groups: one performing medium-intensity strengthening exercises (≥40-60% 1 RM (Repetition Maximum)) and another engaging in low-intensity strengthening exercises (20-30%1RM) with BFR. The BFR technique involved applying a cuff to the upper third of the thigh with a restrictive pressure of 50 mmHg or 40% Artery Occlusion Pressure, which was released during rest periods.Results: The moderate and BFR groups exhibited notable distinctions in all directions (anterior, posterolateral, posteromedial and composite) for both left and right legs (p<0.001). The disparity in LQ-YBT values between groups was notable in the right anterior (p=0.017), right posterolateral (p<0.001), right composite (p<0.001), left anterior (p=0.007), and left composite (p=0.050) directions.Conclusions: This study showed that low-intensity resistance exercise with BFR for six weeks may yield superior improvements in the LQ-YBT for elderly women compared to moderate-intensity strengthening exercises
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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 | 0.000 | 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".