Evidence map›Paper›PMID 33373514›Full record

ArticleAsian spine journal2020

Diagnostic Modality in Spine Disease: A Review.

Gang-Un Kim, Min Cheol Chang, Tae Uk Kim, Gun Woo Lee

Abstract read
In one paragraph

Article in Asian spine journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 2 pooled it
–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

37 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  6. ISSLS Prize in Bioengineering Science 2026: Hidden in Plain Sight: Machine Learning-Assisted MRI Reveals Novel Vertebral Body Biomarkers of Chronic Low Back Pain in Humans.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
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  16. Detection and Localization of Spine Disorders from Plain Radiography.Journal of imaging informatics in medicine · 2024
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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

4 authors.

Gang-Un KimDepartment of Orthopaedic Surgery, Hanil General Hospital, Seoul, Korea.
Min Cheol ChangDepartment of Physical Medicine and Rehabilitation, Yeungnam University College of Medicine, Daegu, Korea.
Tae Uk KimDepartment of Rehabilitation, Dankook University College of Medicine, Cheonan, Korea.
Gun Woo LeeDepartment of Orthopaedic Surgery, Yeungnam University Medical Center, Yeungnam University College of Medicine, Daegu, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spine diseases are common and exhibit several causes, including degeneration, trauma, congenital issues, and other specific factors. Most people experience a variety of symptoms of spine diseases during their lifetime that are occasionally managed with conservative or surgical treatments. Accurate diagnosis of the spine pathology is essential for the appropriate management of spine disease, and various imaging modalities can be used for the diagnosis, including radiography, computed tomography (CT), magnetic resonance imaging (MRI), and other studies such as EOS, bone scan, single photon emission CT/CT, and electrophysiologic test. Patient (or case)-specific selection of the diagnostic modality is crucial; thus, we should be aware of basic information and approaches of the diagnostic modalities. In this review, we discuss in detail, about diagnostic modalities (radiography, CT, MRI, electrophysiologic study, and others) that are widely used for spine disease.

Indexed as

Computed tomographyDiagnostic imagingElectrophysiologic studyMagnetic resonance imagingRadiographySpinal diseases

Identifiers

PMID33373514
PMCPMC7788365

What OpenQuestion holds

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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.