Evidence map›Paper›PMID 41703540›Full record

ArticleBMC musculoskeletal disorders2026

Associations between single and combined lumbar MRI findings and low back pain with and without leg pain: a cross-sectional study.

Line Dragsbaek, Per Kjaer, Rikke Krüger Jensen, Mark Hancock, Lars Peter Korsholm, Tue Secher Jensen

Abstract read
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Article in BMC musculoskeletal disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Line DragsbaekCenter for Muscle and Joint Health, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark. linedragsbaek@health.sdu.dk.
Per KjaerCenter for Muscle and Joint Health, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
Rikke Krüger JensenCenter for Muscle and Joint Health, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
Mark HancockDepartment of Health Sciences and Spinal Pain Research Center, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia.
Lars Peter KorsholmCenter for Muscle and Joint Health, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
Tue Secher JensenCenter for Muscle and Joint Health, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is no established consensus on how to quantify and combine MRI findings to most accurately assess their cumulative relationship with different low back pain (LBP) phenotypes.

objectivesTo explore associations between single MRI findings, sum scores and combinations of findings and LBP with and without leg pain.

methodsCross-sectional analyses from a population-based cohort of 344 people aged 45 years with lumbar MRI and self-reported data. LBP phenotypes were defined as ‘no-LBP’ (n = 198), ‘non-radicular LBP’ (n = 90), and ‘radicular LBP’ (n = 56). Each MRI finding was analysed as present at one or more segmental levels and as sum scores across levels. Two combinations of MRI findings were defined based on their hypothesised relevance to non-radicular or LBP with leg pain. Multinomial logistic regression was used to explore patterns in estimates of association.

resultsDisc degeneration, Modic type II, facet joint degeneration, and abnormal disc contour showed increasing estimates of association with non-radicular LBP when analysed as sum scores and present at more segmental levels. For the non-radicular combination of MRI-findings, participants with ≥ 4 findings had higher estimates of association with non-radicular LBP compared to those with no or fewer findings. For the radicular combination of MRI-findings, participants with ≥ 4 findings had increased estimates of association compared to those with no or fewer findings for both LBP phenotypes.

conclusionAlthough no statistically significant associations were observed, four of seven MRI findings showed increasing estimates of associations with non-radicular LBP when assessed as sum scores. Participants with ≥ 4 MRI findings had increased estimates of association with LBP phenotypes compared to those with no or fewer findings. These observations require confirmation in larger studies.

Indexed as

Intervertebral Disc DegenerationLow Back PainLumbar VertebraeMagnetic Resonance ImagingCross-Sectional StudiesFemaleHumansLegMaleMiddle AgedPhenotypeComined MRI findingsLow back pain phenotypesLumbar spineMagnetic resonance imaging

Identifiers

PMID41703540
PMCPMC13019712

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LicenceCC BY-NC-ND
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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.