Chronic low back pain (CLBP) is the most common chronic pain condition and is often resistant to conventional treatments. Acupuncture is a popular alternative for treating CLBP but its mechanisms of action remain poorly understood. Evidence suggests that pain regulatory mechanisms (particularly the ascending and secondarily the descending pain modulatory pathways) and psychological mechanisms (e.g., expectations, pain catastrophizing and self-efficacy) may be involved in the pathogenesis of CLBP and its response to treatments. We will examine these mechanisms in the treatment of CLBP by electroacupuncture (EA).
We present the aims and methods of a placebo-controlled, participant-blinded and assessor-blinded mechanistic study. Adult patients with CLBP will be randomized to receiving 16 sessions of real (active) or sham (placebo) EA over the course of 8 weeks. The primary pain regulatory measure for which the study was powered is temporal summation (TS), which approximates ascending pain facilitation. Conditioned pain modulation (CPM), representing a descending pain modulatory pathway, will be our secondary pain regulatory measure. The primary psychological measure is expectations of benefit, and the secondary psychological measures are pain catastrophizing and self-efficacy in managing pain. Main clinical outcomes are back pain bothersomeness on a 0–100 visual analog scale (primary), Roland Morris Disability Questionnaire (secondary), and relevant items from the National Institutes of Health (NIH) Patient-Reported Outcome Measures Information System (secondary). We hypothesize that compared to sham, real EA will lead to greater reduction in TS after 8 treatment sessions (4 weeks); and that reduction in TS (and secondarily, increase in CPM) after 8 treatment sessions will mediate reduction in back pain bothersomeness from baseline to week 10 (clinical response) to EA. We also hypothesize that the three psychological factors are moderators of clinical response. With 100 treatment completers, the study is designed to have 80% power to detect a medium-sized between-group effect (d = 0.5) on temporal summation.
Source: Trials, 19(1), 685-685.
Aurthor: Kong, J.-T., MacIsaac, B., Cogan, R., Ng, A., Law, C. S. W., Helms, J., . . . Manber, R. (2018).https://www.ncbi.nlm.nih.gov/pmc/PMC6292023/