Nuances of the Valsalva manoeuvre and bracing with regard to resistance training performance and its effects on the pelvic floor
Bibliographic record
Abstract
There is a great deal of confusion about the use of the Valsalva manoeuvre (VM), and its potential to harm or benefit the pelvic floor when performing resistance training (RT). The VM is completed when expiratory pressure is exerted on a closed or partially closed glottis. This creates a haemodynamic response that corresponds to an increase in blood pressure and then heart rate. For the RT athlete, the VM is a term used to describe bracing of the abdominal musculature to increase trunk stiffness and lumbar stability by intensifying intra-abdominal pressure. This gives individuals a performance advantage during RT. Within pelvic health, the VM is used to assess pelvic floor dysfunction (PFD), and in particular, pelvic organ prolapse. Emerging literature demonstrates that rates of PFD are high in resistance-trained female athletes, and therefore, it has been suggested that avoidance of the VM helps to reduce pelvic floor complaints in this population. However, this is unrealistic given that an involuntary, transient VM occurs at loads greater than 80% of an individual’s one repetition maximum, and removal of the VM would potentially reduce performance in RT athletes. Physiotherapists need to use their evaluation and management skills to improve the symptoms of individuals who participate in RT and experience PFD. This clinical commentary reviews the physiology of the VM, explores rates of PFD in resistance-trained female athletes, and makes recommendations for the evaluation and treatment of these individuals. Unique considerations for the pregnant female participating in RT are also discussed.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".