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Elsevier, Manual Therapy, 4(17), p. 336-344, 2012

DOI: 10.1016/j.math.2012.03.013

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Mechanisms-based classifications of musculoskeletal pain: Part 1 of 3: Symptoms and signs of central sensitisation in patients with low back (+/- leg) pain

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This paper is available in a repository.

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Abstract

As a mechanisms-based classification of pain 'central sensitisation pain' (CSP) refers to pain arising from a dominance of neurophysiological dysfunction within the central nervous system. Symptoms and signs associated with an assumed dominance of CSP 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 CSP 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 three symptoms and one sign predictive of CSP, including: 'Disproportionate, non-mechanical, unpredictable pattern of pain provocation in response to multiple/non-specific aggravating/easing factors', 'Pain disproportionate to the nature and extent of injury or pathology', 'Strong association with maladaptive psychosocial factors (e.g. negative emotions, poor self-efficacy, maladaptive beliefs and pain behaviours)' and 'Diffuse/non-anatomic areas of pain/tenderness on palpation'. This cluster was found to have high levels of classification accuracy (sensitivity 91.8%, 95% confidence interval (CI): 84.5-96.4; specificity 97.7%, 95% CI: 95.6-99.0). Pattern recognition of this empirically-derived cluster of symptoms and signs may help clinicians identify an assumed dominance of CSP in patients with low back pain disorders in a way that might usefully inform their management.