Evidence map›Paper›PMID 29463258›Full record

Observational studyBMC musculoskeletal disorders2018

The association between subgroups of MRI findings identified with latent class analysis and low back pain in 40-year-old Danes.

Rikke K Jensen, Peter Kent, Tue S Jensen, Per Kjaer

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC musculoskeletal disorders, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact, top 100% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Observational
  5. Review
  6. Review
  7. Article
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  9. Review
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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 at 4 institutions in 2 countries.

Rikke K JensenInstitute of Regional Health Research, University of Southern Denmark, Odense, Denmark. rikke.kruger.jensen@rsyd.dk.
Peter KentDepartment of Physiotherapy and Exercise Science, Curtin University, Perth, Australia.
Tue S JensenInstitute of Regional Health Research, University of Southern Denmark, Odense, Denmark.
Per KjaerDepartment of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
Curtin University · AULillebaelt Hospital · DKPsykiatrien i Region Syddanmark · DKUniversity of Southern Denmark · DK

Funding

Foundation for Chiropractic Research and Post Graduate Education 09/74
6 · The paper itself

Abstract

backgroundResearch into the clinical importance of spinal MRI findings in patients with low back pain (LBP) has primarily focused on single imaging findings, such as Modic changes or disc degeneration, and found only weak associations with the presence of pain. However, numerous MRI findings almost always co-exist in the lumbar spine and are often present at more than one lumbar level. It is possible that multiple MRI findings are more strongly associated with LBP than single MRI findings. Latent Class Analysis is a statistical method that has recently been tested and found useful for identifying latent classes (subgroups) of MRI findings within multivariable datasets. The purpose of this study was to investigate the association between subgroups of MRI findings and the presence of LBP in people from the general population.

methodsTo identify subgroups of lumbar MRI findings with potential clinical relevance, Latent Class Analysis was initially performed on a clinical dataset of 631 patients seeking care for LBP. Subsequently, 412 participants in a general population cohort (the 'Backs on Funen' project) were statistically allocated to those existing subgroups by Latent Class Analysis, matching their MRI findings at a segmental level. The subgroups containing MRI findings from the general population were then organised into hypothetical pathways of degeneration and the association between subgroups in the pathways and the presence of LBP was tested using exact logistic regression.

resultsSix subgroups were identified in the clinical dataset and the data from the general population cohort fitted the subgroups well, with a median posterior probability of 93%-100%. These six subgroups described two pathways of increasing degeneration on upper (L1-L3) and lower (L4-L5) lumbar levels. An association with LBP was found for the subgroups describing severe and multiple degenerative MRI findings at the lower lumbar levels but none of the other subgroups were associated with LBP.

conclusionAlthough MRI findings are common in asymptomatic people and the association between single MRI findings and LBP is often weak, our results suggest that subgroups of multiple and severe lumbar MRI findings have a stronger association with LBP than those with milder degrees of degeneration.

Indexed as

AdultCohort StudiesCross-Sectional StudiesDenmarkFemaleHumansLow Back PainMagnetic Resonance ImagingMaleSurveys and QuestionnairesLatent class analysisLow back painMRISubgroups

Identifiers

PMID29463258
PMCPMC5819254
OpenAlexW2596806033

What OpenQuestion holds

Textmetadata
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.