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Updated: Jan 25, 2026

Dynamic Quantitative Sensory Testing to Characterize Central Pain Processing
Published on: February 16, 2017
Quantitative sensory testing and predicting outcomes for musculoskeletal pain, disability, and negative affect: a
Vasileios Georgopoulos1,2, Kehinde Akin-Akinyosoye1,2, Weiya Zhang1,2,3
1Department of Academic Rheumatology, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, United Kingdom.
Abstract:
Hypersensitivity due to central pain mechanisms can influence recovery and lead to worse clinical outcomes, but the ability of quantitative sensory testing (QST), an index of sensitisation, to predict outcomes in chronic musculoskeletal disorders remains unclear. We systematically reviewed the evidence for ability of QST to predict pain, disability, and negative affect using searches of CENTRAL, MEDLINE, EMBASE, AMED, CINAHL, and PubMed databases up to April 2018. Title screening, data extraction, and methodological quality assessments were performed independently by 2 reviewers. Associations were reported between baseline QST and outcomes using adjusted (β) and unadjusted (r) correlations. Of the 37 eligible studies (n = 3860 participants), 32 were prospective cohort studies and 5 randomised controlled trials. Pain was an outcome in 30 studies, disability in 11, and negative affect in 3. Meta-analysis revealed that baseline QST predicted musculoskeletal pain (mean r = 0.31, 95% confidence interval [CI]: 0.23-0.38, n = 1057 participants) and disability (mean r = 0.30, 95% CI: 0.19-0.40, n = 290 participants). Baseline modalities quantifying central mechanisms such as temporal summation and conditioned pain modulation were associated with follow-up pain (temporal summation: mean r = 0.37, 95% CI: 0.17-0.54; conditioned pain modulation: mean r = 0.36, 95% CI: 0.20-0.50), whereas baseline mechanical threshold modalities were predictive of follow-up disability (mean r = 0.25, 95% CI: 0.03-0.45). Quantitative sensory testing indices of pain hypersensitivity might help develop targeted interventions aiming to improve outcomes across a range of musculoskeletal conditions.
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