Evidence map›Paper›PMID 37875368›Full record

ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2023

Research progress in pelvic floor ultrasound for assessing the morphology and function of levator ani muscle in women.

Duo Li, Rong Lu

Abstract read
In one paragraph

Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. [Deep learning models based on fused ultrasound images for the assessment of cystocele in women].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
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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.

Duo LiDepartment of Ultrasonography, Xiangya Hospital, Central South University, Changsha 410008. liduo991124@163.com.
Rong LuDepartment of Gynecology, Xiangya Hospital, Central South University, Changsha 410008, China. 1752020522@qq.com.

Funding

the Natural Science Foundation of Hunan Province, China 2023JJ30920
6 · The paper itself

Abstract

Pelvic floor ultrasound can clearly visualize the position and morphology of pelvic floor organs, observe the pelvic organ prolapse in real-time, and quantify and analyze the degree of the levator ani muscle injury, which is the most common imaging method to assess the morphology and function of the levator ani muscle to date. The different ultrasound imaging techniques provide a variety of indicators, each with its own advantages and limitations.Furthermore, two-dimensional ultrasound is the basis of imaging, but it fails to detect cross-sectional images of the pelvic floor; three-dimensional ultrasound can acquire the axial plane of the levator hiatus; tomographic ultrasound imaging allows real-time observation of the levator ani muscle injury; shear wave elastography can provide a quantitative assessment of the contractility and elastic characteristics of the levator ani muscle in real-time. It is of great significance to summarize the basic principles of various ultrasound imaging techniques, summarize the ultrasound image characteristics of levator ani muscle and its hiatus in different populations and different states, and explore the cut-off values and diagnostic criteria-related ultrasound parameters for improving the diagnostic efficiency of pelvic floor ultrasound for levator ani muscle injury, leading to reducing missed diagnosis and misdiagnosis of lesions.

Indexed as

Pelvic FloorPelvic Organ ProlapseFemaleHumansImaging, Three-DimensionalUltrasonographylevator ani musclepelvic floorultrasound

Identifiers

PMID37875368
PMCPMC10930840

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.