Posterior to anterior spinal stiffness measured in a sample of 127 secondary care low back pain patients.

Abstract

The sensation of spinal stiffness is a commonly reported symptom among back pain patients, with the clinical assessment of spinal stiffness usually being part of the decision-making process when deciding on providing manual treatment of low back pain. While any relationship between spinal stiffness and low back pain is likely to be multifactorial, prior exploration of this relationship has been overly simplistic (e.g., univariate regression analyses). The purpose of this study was to address this gap by taking a broader approach to compare instrumented measures of spinal stiffness to demographic characteristics, pain phenotypes, psychometrics, and spine-related disability in a sample of secondary care low back pain patients using multivariate regression analysis. Instrumented spinal stiffness measures from 127 patients in secondary care were used to calculate terminal and global spinal stiffness scores. A best subset analysis was used to find the subsets of 14 independent variables that most accurately predicted stiffness based on the evaluation of the adjusted R-square, Akaike Information Criteria, and the Bayesian Information Criteria. In the resulting multivariate models, sex (p < 0.001) and age (p < 0.001) were the primary determinants of terminal stiffness, while global stiffness was primarily determined by age (p = 0.003) and disability (p = 0.024). Instrumented measures of spinal stiffness are multifactorial in nature, and future research into this area should make use of multivariate analyses.