• Kosuke Saita, Masahiko Sumitani, Takuya Nikaido, Miho Sekiguchi, Reo Inoue, Hiroaki Abe, Shinichi Konno, and Kanji Uchida.
• Department of Anesthesiology and Pain Relief Center, The University of Tokyo Hospital, Tokyo, Bunkyo-ku, Japan.
• Curr Med Res Opin. 2021 Aug 1; 37 (8): 1341-1348.

BackgroundNeuropathic components and catastrophic thoughts contribute to the quality of life impairments in patients with chronic pain. This retrospective cross-sectional observational study examined the extent to which neuropathic components affect pain intensity and catastrophic thoughts using a mathematical model.MethodsParticipants with chronic pain with spinal or joint disorders were rated for pain intensity using a numerical rating scale (NRS), painDETECT questionnaire (PDQ), and pain catastrophizing scale (PCS). We plotted to scatter plots between PDQ and either NRS or PCS and drew best-fit lines for patients with leg pain only. We divided patients with both leg and back pain into two clusters: located above or below the baselines, and then we drew the best-fit lines for each cluster. We performed factor analysis on PDQ items and developed and validated a discriminant to identify patients located above the baseline in another cohort of musculoskeletal disorders.ResultsWe analyzed 163 patients with lumbar disorders and 205 patients with joint disorders. PDQ correlated exponentially with NRS and PCS of the patients located above the baseline in both disorder groups and correlated linearly or logarithmically in patients located below the baseline. Factor analysis revealed three sets of pain characteristics for each disorder. We developed the discriminant from PDQ items to identify patients showing exponential correlations and then validated it in another cohort of 137 patients. The coefficient for "pressure-evoked pain" was the highest in the discriminant.ConclusionsMathematical models indicate neuropathic components demonstrate linear correlations with NRS and PCS generally, but exponential correlations in a cluster of the patients with musculoskeletal pain. We developed and validated the discriminant based on pain characteristics to identify such patients; "pressure-evoked pain" was the most significant contributor.

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