Evidence map›Paper›PMID 40751839›Full record

ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2025

Digital pain diagrams to identify common lumbar spinal stenosis pain distribution patterns: a cross-sectional latent class analysis.

James J Young, Natalie Hong Siu Chang, Casper Nim, Søren O Neill, David T McNaughton, Rikke Krüger Jensen, Steen Harsted

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Article in 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, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers 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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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.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

James J YoungUniversity Health Network, Toronto, Canada. james.young2@uhn.ca.
Natalie Hong Siu ChangUniversity of Southern Denmark, Odense, Denmark.
Casper NimUniversity of Southern Denmark, Odense, Denmark.
Søren O NeillUniversity of Southern Denmark, Odense, Denmark.
David T McNaughtonCentral Queensland University, Rockhampton, Australia.
Rikke Krüger JensenUniversity of Southern Denmark, Odense, Denmark.
Steen HarstedUniversity of Southern Denmark, Odense, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo identify common pain distribution patterns on digital pain diagrams (PDs) in patients with lumbar spinal stenosis (LSS) presenting to a secondary spine care setting.

methodsPatients presenting to a secondary spine center with a diagnostic code for LSS and a completed PD were included. Latent class analysis of PDs was used to identify unique pain distribution patterns. The final class solution was selected based on the most suitable combination of the Bayesian Information Criterion, posterior probabilities, minimum class size, and the clinical interpretability of the LSS pain pattern distributions.

resultsA total of 2,379 patients with LSS were included. A six-class model of LSS pain distribution patterns was the preferred model solution. Class 1 (11.4%) represented a bilateral posterior leg pain (11.4%) distribution pattern; Class 2 (8.7%) bilateral posterior and anterior leg pain; Class 3 (26.1%) unilateral posterior leg pain; Class 4 (21.0%) unilateral posterior leg pain with low back pain; Class 5 (22.9%) unilateral anterior and posterior leg pain; and Class 6 (9.9%) multisite pain.

conclusionWe identified clinically recognizable pain distribution patterns in patients with LSS presenting to a secondary spine center in Denmark. These preliminary pain distribution patterns may represent clinical LSS phenotypes, but at minimum suggest that heterogenous pain presentations are common in people with LSS. Future work is needed to validate these pain distribution patterns in other LSS samples and determine their relationship with diagnostic and treatment outcomes.

Indexed as

Low Back PainLumbar VertebraePain MeasurementSpinal StenosisAgedCross-Sectional StudiesFemaleHumansLatent Class AnalysisMaleMiddle AgedLumbar spinal stenosisPain diagramsPain distribution

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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 Socratic graph.