Chronic low back pain is a common and disabling musculoskeletal condition that may involve different underlying pain mechanisms. Mechanism-based pain phenotyping may facilitate a better understanding of individual pain presentations and contribute to more personalized management strategies.
In this cross-sectional observational study, individuals with chronic low back pain will undergo a comprehensive clinical assessment. Pain phenotypes will be determined using a contemporary clinical pain phenotyping algorithm based on criteria for nociceptive, neuropathic, and nociplastic pain. Participants presenting features of more than one pain mechanism will be classified as having mixed pain.
Assessment will include a detailed clinical history, quantitative sensory assessment, pain intensity and distribution, neuropathic pain characteristics, central sensitization-related symptoms, low back pain-related disability, health-related quality of life, and pain catastrophizing. Quantitative sensory assessment will include static tactile mechanical detection, thermal perception, static mechanical allodynia, dynamic mechanical allodynia, and vibration perception.
The study will also examine the intra-rater and inter-rater reliability of the pain phenotyping algorithm using standardized case scenarios derived from participants' clinical assessments.