Evidence map›Paper›PMID 38339435›Full record

ArticleSensors (Basel, Switzerland)2024

Assessment of the Performance of Ultrasonography for Detecting Myofascial Trigger Points.

Han-Yu Chen, Chang-Zern Hong, Yueh-Ling Hsieh

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 20% of its field
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

6 citing papers in PubMed, 5 citations in OpenAlex.

  1. Trial
  2. Review
  3. Review
  4. Article
  5. Article
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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

3 authors at 2 institutions in 1 country.

Han-Yu ChenDepartment of Physical Therapy, Hungkuang University, Taichung 433304, Taiwan.ORCID 0000-0002-4754-3024
Chang-Zern HongTaiwan Myopain Academic Association, Tainan 704032, Taiwan.
Yueh-Ling HsiehDepartment of Physical Therapy, China Medical University, Taichung 406040, Taiwan.ORCID 0000-0002-8507-170X
China Medical University · TWHungkuang University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Needle electromyogram (EMG) research has suggested that endplate noise (EPN) is a characteristic of myofascial trigger points (MTrPs). Although several studies have observed MTrPs through ultrasonography, whether they are hyperechoic or hypoechoic in ultrasound images is still controversial. Therefore, this study determined the echogenicity of MTrP ultrasonography. In stage 1, the MTrP of rat masseter muscle was identified through palpation and marked. Needle EMG was performed to detect the presence of EPN. When EPN was detected, ultrasound scans and indwelling needles were used to identify the nodule with a different grayscale relative to that of its surrounding tissue, and the echogenicity of the identified MTrP was determined. In stage 2, these steps were reversed. An ultrasound scan was performed to detect the nodule at the marked site, and an EMG needle was inserted into the nodule to detect EPN. There were 178 recordings in each stage, obtained from 45 rats. The stage 1 results indicate that the MTrPs in ultrasound images were hypoechoic with a 100% sensitivity of assessment. In stage 2, the accuracy and precision of MTrP detection through ultrasonography were 89.9% and 89.2%, respectively. The results indicate that ultrasonography produces highly accurate and precise MTrP detection results.

Indexed as

Myofascial Pain SyndromesTrigger PointsAnimalsElectromyographyNeedlesRatsUltrasonographyechogenicityendplate noisemyofascial trigger pointultrasonography

Identifiers

PMID38339435
PMCPMC10857038
OpenAlexW4391136646

What OpenQuestion holds

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LicenceCC BY
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.