Evidence map›Paper›PMID 41526700›Full record

Observational studyInternational urogynecology journal2026

Artificial Intelligence for the Automated Measurement of Hiatal Dimensions.

Hans Peter Dietz, Ka Lai Shek

Abstract readObservational Study
PubMed Publisher
In one paragraph

Observational study in International urogynecology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hans Peter DietzSydney Urodynamic Centres, Sydney, Australia. hpdietz2@bigpond.com.ORCID http://orcid.org/0000-0002-2211-6149
Ka Lai ShekLiverpool Clinical School, Western Sydney University, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introduction and hypothesisThe levator hiatus is an important determinant of pelvic organ prolapse and prolapse recurrence after surgery. Manufacturers are now offering automatic determination of hiatal dimensions.

methodsThis was an observational study using data sets of 437 women attending a urogynaecological unit in 2024 and 2025. All had 4D pelvic floor ultrasound using a Voluson E 22 system with SonoPelvic™ software. Data sets obtained on Valsalva were used for automated measurements. Manual measurements were performed later on stored data sets blinded against all other data. For statistical analysis we employed ICC and Bland Altman plots. Patients in whom measurements differed by ≥20% were reviewed.

resultsThe 437 women seen during the study period presented with stress urinary incontinence (n = 304), urgency urinary incontinence (n = 334) and symptoms of pelvic organ prolapse (n = 229). Automated measurements yielded a mean of 25.45 (4.08-64.76) cm

conclusionAutomated analysis by the current version of SonoPelvic™ shows a strong correlation with manual measurements, except in women with highly abnormal pelvic organ support. The software is under continuous development for which several recommendations are made.

Indexed as

Artificial IntelligencePelvic FloorPelvic Organ ProlapseAdultAgedFemaleHumansIntelligent SystemsMiddle AgedUltrasonographyUrinary Incontinence, Stress3D/4D ultrasoundArtificial intelligenceAutomated analysisLevator aniLevator hiatusPelvic organ prolapse

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.