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    Mechanisms-based classifications of musculoskeletal pain: part 2 of 3: symptoms and signs of peripheral neuropathic pain in patients with low back (± leg) pain.

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    Authors
    Smart, Keith M
    Blake, Catherine
    Staines, Anthony
    Thacker, Mick
    Doody, Catherine
    Affiliation
    Physiotherapy Department, St Vincent's University Hospital, Elm Park, Dublin 4, Ireland. k.smart@svuh.ie
    Issue Date
    2012-08
    MeSH
    Adult
    Aged
    Aged, 80 and over
    Analysis of Variance
    Bayes Theorem
    Cluster Analysis
    Cross-Sectional Studies
    Female
    Humans
    Ireland
    Low Back Pain
    Male
    Middle Aged
    Musculoskeletal Pain
    Nociceptive Pain
    Peripheral Nervous System Diseases
    Sensitivity and Specificity
    Severity of Illness Index
    Young Adult
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    Citation
    Mechanisms-based classifications of musculoskeletal pain: part 2 of 3: symptoms and signs of peripheral neuropathic pain in patients with low back (± leg) pain. 2012, 17 (4):345-51 Man Ther
    Journal
    Manual therapy
    URI
    http://hdl.handle.net/10147/251281
    DOI
    10.1016/j.math.2012.03.003
    PubMed ID
    22465002
    Abstract
    As a mechanisms-based classification of pain 'peripheral neuropathic pain' (PNP) refers to pain arising from a primary lesion or dysfunction in the peripheral nervous system. Symptoms and signs associated with an assumed dominance of PNP in patients attending for physiotherapy have not been extensively studied. The purpose of this study was to identify symptoms and signs associated with a clinical classification of PNP in patients with low back (± leg) pain. Using a cross-sectional, between-subjects design; four hundred and sixty-four patients with low back (± leg) pain were assessed using a standardised assessment protocol. Patients' pain was assigned a mechanisms-based classification based on experienced clinical judgement. Clinicians then completed a clinical criteria checklist specifying the presence or absence of various clinical criteria. A binary logistic regression analysis with Bayesian model averaging identified a cluster of two symptoms and one sign predictive of PNP, including: 'Pain referred in a dermatomal or cutaneous distribution', 'History of nerve injury, pathology or mechanical compromise' and 'Pain/symptom provocation with mechanical/movement tests (e.g. Active/Passive, Neurodynamic) that move/load/compress neural tissue'. This cluster was found to have high levels of classification accuracy (sensitivity 86.3%, 95% CI: 78.0-92.3; specificity 96.0%, 95% CI: 93.4-97.8; diagnostic odds ratio 150.9, 95% CI: 69.4-328.1). Pattern recognition of this empirically-derived cluster of symptoms and signs may help clinicians identify an assumed dominance of PNP mechanisms in patients with low back pain disorders in a way that might usefully inform subsequent patient management.
    Item Type
    Article
    Language
    en
    ISSN
    1532-2769
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.math.2012.03.003
    Scopus Count
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