Quantification of pelvic floor muscle strength in female urinary incontinence: A systematic review and comparison of contemporary methodologies
Bibliographic record
Abstract
AIMS: There remains no gold standard for quantification of voluntary pelvic floor muscle (PFM) strength, despite international guidelines that recommend PFM assessment in females with urinary incontinence (UI). Methods currently reported for quantification of skeletal muscle strength across disciplines are systematically reviewed and their relevance for clinical and academic use related to the pelvic floor are described. METHODS: A systematic review via Medline, PubMed, CINHAL, and the Cochrane database using key terms for pelvic floor anatomy and function were cross referenced with skeletal muscle strength quantification from 1946 to 2016. Full text peer-reviewed articles in English having female subjects with incontinence were identified. Each study was analyzed for use of controls, type of methodology as direct or indirect measures, benefits, and limitations of the technique. RESULTS: A total of 1586 articles were identified of which 50 met the inclusion criteria. Nine methodologies of determining PFM strength were described including: digital palpation, perineometer, dynamometry, EMG, vaginal cones, ultrasonography, magnetic resonance imaging, urine stream interruption test, and the Colpexin pull test. Thirty-two percent lacked a control group. CONCLUSION: Technical refinements in both direct and indirect instrumentation for PFM strength measurement are allowing for sensitivity. However, the most common methods of quantification remain digital palpation and perineometry; techniques that pose limitations and yield subjective or indirect measures of muscular strength. Dynamometry has potential as an accurate and sensitive tool, but is limited by inability to assess PFM strength during dynamic movements.
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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 | 0.017 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.022 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".