Evidence map›Paper›PMID 40035340›Full record

ArticleEuropean journal of pain (London, England)2025

Subgrouping People With Acute Low Back Pain Based on Psychological, Sensory, and Motor Characteristics: A Cross-Sectional Study.

Patrick Ippersiel, Claudia Côté-Picard, Jean-Sébastien Roy, Hugo Massé-Alarie

Abstract read
In one paragraph

Article in European journal of pain (London, England), 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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0cells of the map it votes in
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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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

4 authors.

Patrick IppersielSchool of Physical and Occupational Therapy, McGill University, Quebec, Canada.ORCID https://orcid.org/0000-0001-6432-8118
Claudia Côté-PicardCenter for Interdisciplinary Research in Rehabilitation and Social Integration, Laval University, Quebec City, Quebec, Canada.
Jean-Sébastien RoyCenter for Interdisciplinary Research in Rehabilitation and Social Integration, Laval University, Quebec City, Quebec, Canada.
Hugo Massé-AlarieCenter for Interdisciplinary Research in Rehabilitation and Social Integration, Laval University, Quebec City, Quebec, Canada.ORCID https://orcid.org/0000-0003-4472-9656

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClustering helps identify patient subgroups with similar biopsychosocial profiles in acute low-back pain (LBP). Motor factors are common treatment targets and are associated with disability but have not been included in acute LBP cluster development. This study aimed to identify subgroups of individuals with acute LBP based on motor, sensory and psychological characteristics and to compare these subgroups regarding clinical outcomes.

methodsNinety-nine participants with acute LBP were recruited, and motor (bending range of motion [ROM], flexion relaxation), pain sensitivity (pressure-pain thresholds, temporal summation of pain) and psychological factors (pain catastrophising, kinesiophobia, self-efficacy) were measured, along with pain, disability and demographics.

resultsPrincipal component analysis accounted for 66.03% of the variance. Four component scores were entered in a hierarchical linear clustering model, deriving 3 subgroups ('mild features' n = 39, 'sensorimotor' n = 35 and 'psychomotor' n = 25). Between-cluster comparisons revealed significant differences in motor, sensory and psychological variables (p < 0.05). Sensorimotor and psychomotor clusters had higher flexion-relaxation ratios (mean difference: > 0.2), greater disability (mean difference: > 7/100) and smaller ROM (mean difference: 7 cm) compared to the 'mild' group. The sensorimotor cluster mostly exhibited higher temporal summation of pain (mean difference: > 1.3/10) and lower pressure-pain thresholds (mean difference: > 1.2 kg/cm

conclusionFindings indicate 3 subgroups, suggesting that motor factors may add granularity to acute LBP clusters. Stratified care based on these subgroups may help refine treatment pathways for acute LBP. SIGNIFICANCE STATEMENT: Including motor factors in cluster development adds a clinically relevant metric to describe people with acute LBP and generates insight into underlying mechanisms of motor adaptation. Longitudinal testing is required to see if these subgroups are differentially related to short- and long-term pain and disability.

Indexed as

Acute PainLow Back PainPain ThresholdAdultCatastrophizationCluster AnalysisCross-Sectional StudiesDisability EvaluationFemaleHumansMaleMiddle AgedPain MeasurementRange of Motion, ArticularSelf EfficacyYoung Adultacute low‐back painmotor adaptionpain sensitivitypsychological factorsrehabilitation

Identifiers

PMID40035340
PMCPMC11877624

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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.