Effects of Blood Flow Restriction Therapy for Muscular Strength, Hypertrophy, and Endurance in Healthy and Special Populations: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVES: Blood flow restriction (BFR) training is an increasingly applied tool with potential benefits in muscular hypertrophy, strength, and endurance. This study investigates the effectiveness of BFR training relative to other forms of training on muscle strength, hypertrophy, and endurance. DATA SOURCES: We performed systematic searches of MEDLINE, Embase, and PubMed and assessed the methodological quality of included studies using the Cochrane risk of bias tool. MAIN RESULTS: We included 53 randomized controlled trials with 31 included in meta-analyses. For muscular strength comparing low-intensity BFR (LI-BFR) training with high-intensity resistance training (HIRT), the pooled mean difference (MD) for 1 repetition maximum was 5.34 kg (95% CI, 2.58-8.09; P < 0.01) favoring HIRT. When comparing LI-BFR training with HIRT for torque, the MD was 6.35 N·m (95% CI, 0.5-12.3; P = 0.04) also favoring HIRT. However, comparing LI-BFR with low-intensity resistance training (LIRT) for torque, there was a MD of 9.94 N·m (95% CI, 5.43-14.45; P < 0.01) favoring BFR training. Assessing muscle hypertrophy, the MD in cross-sectional area was 0.96 cm2 (95% CI, 0.21-1.7; P = 0.01) favoring pooled BFR training compared with nonocclusive training. Assessing endurance, V̇o2 maximum demonstrated a greater mean increase of 0.37 mL/kg/min (95% CI, -0.97 to 3.17; P = 0.64) in BFR endurance training compared with endurance training alone. CONCLUSION: Blood flow restriction training produced increases in muscular strength, hypertrophy, and endurance. Comparing LI-BFR training with HIRT, HIRT was a significantly better training modality for increasing muscle hypertrophy and strength. However, LI-BFR was superior when compared with a similar low-intensity protocol. Blood flow restriction training is potentially beneficial to those unable to tolerate the high loads of HIRT; however, better understanding of its risk to benefit ratio is needed before clinical application. LEVEL OF EVIDENCE: Level 1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.019 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".