• David M Walton, Timothy S H Kwok, Swati Mehta, Eldon Loh, Ashley Smith, James Elliott, Steven J Kamper, Helge Kasch, and Michele Sterling.
• *Faculty of Health Sciences †Schulich School of Medicine and Dentistry, Western University, London, ON, Canada §Feinberg School of Medicine, Northwestern University, Chicago, IL ‡Menzies Health Institute, Griffith University, Southport, Qld ∥George Institute for Global Health, Sydney, NSW, Australia ¶Department of Neurology, Aarhus University, Aarhus, Denmark.
• Clin J Pain. 2017 May 1; 33 (5): 422-428.

ObjectiveTo determine pressure pain detection threshold (PPDT) related phenotypes of individuals with mechanical neck pain that may be identifiable in clinical practice.MethodsThis report describes a secondary analysis of 5 independent, international mechanical neck pain databases of PPDT values taken at both a local and distal region (total N=1176). Minor systematic differences in mean PPDT values across cohorts necessitated z-transformation before analysis, and each cohort was split into male and female sexes. Latent profile analysis (LPA) using the k-means approach was undertaken to identify the most parsimonious set of PPDT-based phenotypes that were both statistically and clinically meaningful.ResultsLPA revealed 4 distinct clusters named according to PPDT levels at the local and distal zones: low-low PPDT (67%), mod-mod (25%), mod-high (4%), and high-high (4%). Secondary predictor variables were evaluated for intracluster and cross-cluster significance. Low-low cluster was most affected, as indicated by pain intensity, disability, and catastrophization scores all significantly above the cohort-specific and sex-specific mean, and active range of motion scores significantly below the mean.DiscussionThe results suggest that there are a large proportion of people with neck pain that present with signs indicating dysfunction beyond the local tissues. Ongoing exploration of these presentations may lead to more informed management and improved outcomes.

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