An automated intravaginal dynamometer: Reliability metrics and the impact of testing protocol on active and passive forces measured from the pelvic floor muscles
Bibliographic record
Abstract
AIMS: (1) To determine the reliability of an automated dynamometer designed to assess pelvic floor muscle (PFM) strength and resistance to passive elongation. (2) To evaluate the impact of PFM length and rate of tissue elongation on dynamometric outcomes. METHODS: At each of two sessions, twenty nulliparous women performed three maximum voluntary contractions (MVC) of their PFMs with the dynamometer set to two different anteroposterior (AP) diameters (25 mm, 35 mm). Next, with PFMs relaxed, the arms of the dynamometer opened three times to 40 mm at two speeds (25 mm/s, 50 mm/s). Outcomes included baseline force, peak force, relative peak force, rate of force development (RFD), stiffness and stress relaxation. Repeated-measures ANOVAs were used to test trial, day, and task effects (α = 0.05), and intra-class correlation coefficients (ICCs) were computed. RESULTS: Forces measured on MVC were higher with the larger AP diameter, and passive resistance was higher for the faster rate of tissue elongation. The between-trial reliability of all outcomes was excellent (0.82 < ICC < 0.98) for all measures except for peak force during the passive elongation task (0.56 < ICC < 0.93). Between-day reliability was good to excellent for active and passive RFD (0.75 < ICC < 0.93), stiffness (ICC = 0.77) and relative peak force (0.71 < ICC < 0.87); absolute force (0.11 < ICC < 0.85) and stress relaxation responses (0.19 < ICC < 0.98) tended to be less reliable. CONCLUSIONS: The reliability of the dynamometer is adequate for both clinical and research applications. Relative forces were more reliable than absolute forces. Dimensions and rate of tissue elongation should be controlled and reported with all pelvic floor muscle assessments as these parameters impact outcomes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".