Evidence map›Paper›PMID 34768665›Full record

ArticleJournal of clinical medicine2021

A Novel Method of Temporomandibular Joint Hypermobility Diagnosis Based on Signal Analysis.

Justyna Grochala, Dominik Grochala, Marcin Kajor, Joanna Iwaniec, Jolanta E Loster, Marek Iwaniec

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Justyna GrochalaDepartment of Prosthodontics, Institute of Dentistry, Jagiellonian University Medical College, Jagiellonian University, 31-155 Kraków, Poland.ORCID 0000-0003-0561-9681
Dominik GrochalaInstitute of Electronics, AGH University of Science and Technology, 30-059 Kraków, Poland.ORCID 0000-0001-9970-710X
Marcin KajorFaculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology, 30-059 Kraków, Poland.
Joanna IwaniecDepartment of Robotics and Mechatronics, Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, 30-059 Kraków, Poland.ORCID 0000-0002-2320-1417
Jolanta E LosterDepartment of Prosthodontics, Institute of Dentistry, Jagiellonian University Medical College, Jagiellonian University, 31-155 Kraków, Poland.ORCID 0000-0002-8759-0810
Marek IwaniecDepartment of Process Control, Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, 30-059 Kraków, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the temporomandibular joint (TMJ) being a well-known anatomical structure its diagnosis may become difficult because physiological sounds accompanying joint movement can falsely indicate pathological symptoms. One example of such a situation is temporomandibular joint hypermobility (TMJH), which still requires comprehensive study. The commonly used official research diagnostic criteria for temporomandibular disorders (RDC/TMD) does not support the recognition of TMJH. Therefore, in this paper the authors propose a novel diagnostic method of TMJH based on the digital time-frequency analysis of sounds generated by TMJ. Forty-seven volunteers were diagnosed using the RDC/TMD questionnaire and auscultated with the Littmann 3200 electronic stethoscope on both sides of the head simultaneously. Recorded TMJ sounds were transferred to the computer via Bluetooth

Indexed as

auscultationhypermobile temporomandibular joint movementRDC/TMDsignal analysisstethoscope

Identifiers

PMID34768665
PMCPMC8584382

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Registered trials

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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.