Evidence map›Paper›PMID 39992136›Full record

ArticleEuropean journal of translational myology2025

Ultrasound

Samra Pjanić, Goran Talić, Nikola Jevtić, Filip Golić, Ivan Soldatović, Nachiappan Chockalingam

Abstract read
In one paragraph

Article in European journal of translational myology, 2025. 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

6 authors.

Samra PjanićInstitute for Physical Medicine, Rehabilitation and Orthopedic Surgery "Dr Miroslav Zotovic", Banja Luka. samra.pjanic@hotmail.com.
Goran TalićInstitute for Physical Medicine, Rehabilitation and Orthopedic Surgery "Dr Miroslav Zotovic", Banja Luka. kancelarija.direktora@ms.zotovicbl.org.
Nikola JevtićScolio Centar, Novi Sad. njevticns@gmail.com.
Filip GolićInstitute for Physical Medicine, Rehabilitation and Orthopedic Surgery "Dr Miroslav Zotovic", Banja Luka. filipgolic@yahoo.com.
Ivan SoldatovićFaculty of Medicine, University of Belgrade, Beograd. ivan.soldatovic@med.bg.ac.rs.
Nachiappan ChockalingamCentre for Biomechanics and Rehabilaition Technologies, Staffordshire University, Stoke-on-Trent, United Kingdom; Faculty of Health Sciences, University of Malta, Msida. n.chockalingam@staffs.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This retrospective study, utilising prospectively collected data, investigates the use of spine ultrasound as an alternative method for assessing scoliosis, with the aim of reducing radiation exposure. We included 92 patients aged 10 to 16 years with suspected idiopathic scoliosis. Exclusion criteria were weight over 150 kg, metal implants, pre-existing conditions, secondary deformities, and cognitive impairments. Each patient underwent clinical assessment and full spine radiographs, followed by spine ultrasound using the Scolioscan® system. Unprocessed B-mode ultrasound images were analysed using automatic measurements. The correlation between Ultrasound Coronal Angle (UCA) and Radiographic Cobb Angle (RCA) was evaluated at initial and follow-up visits. Strong correlations were found between UCA and RCA, with correlation coefficients ranging from 0.786 to 0.903 (p<0.001). The regression formula showed good predictive accuracy for curve progression on follow-up radiographs. The best results were observed in females and in primary thoracic curves (r = 0.936, p<0.001). Although only four patients exhibited true progression (≥5° increase in Cobb angle), changes in scoliotic angles were effectively detected using ultrasound. This study confirms the feasibility of unprocessed spine ultrasound for scoliosis monitoring in clinical settings. Automatic measurements without 3D reconstruction make ultrasound a practical tool for tracking progression. The regression model shows potential for predicting curve progression, although further validation is needed. These findings suggest spine ultrasound could reduce the need for radiographs, benefiting patients by minimising radiation exposure while providing reliable monitoring of scoliosis progression and treatment outcomes.

Identifiers

PMID39992136
PMCPMC12038569

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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.