Pelvic Floor Ultrasound Imaging: Are Physiotherapists Interchangeable in the Assessment of Levator Hiatal Biometry?
Bibliographic record
Abstract
PURPOSE: To evaluate inter-examiner reliability in the ultrasound (US) assessment of levator hiatal dimensions when different physiotherapists perform independent data acquisition and analysis. METHODS: In this cross-sectional observational study, 14 asymptomatic nulliparous women were imaged at rest, during pelvic floor muscle contraction, and during Valsalva manoeuvre by two physiotherapists using three-dimensional (3D) and four-dimensional (4D) transperineal US. Examiners each measured the dimensions of the levator hiatus (area and antero-posterior and transverse diameters) from the US volumes they respectively acquired. Inter-examiner reliability was determined using intra-class correlation coefficients (ICCs), and inter-examiner agreement was determined using Bland-Altman analyses. RESULTS: The ICC results demonstrated very good inter-examiner reliability (ICC=0.84-0.98); Bland-Altman results showed high inter-examiner agreement across all measurements. CONCLUSIONS: Trained examiners may be considered interchangeable in the US assessment of levator hiatal biometry. Overall, trained physiotherapists using transperineal US imaging to assess levator hiatal biometry can be confident when comparing their own clinical findings to those of their colleagues and to findings published in the literature.
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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 | 0.039 | 0.164 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".