The power of integrating data: advancing pain research using meta-analysis

Effectiveness of neural mobilisation for the treatment of nerve-related cervicobrachial pain: a systematic review with subgroup meta-analysis

ABSTRACT

Neural mobilisations (NM) have been advocated for the treatment of nerve-related cervicobrachial pain; however, it is unclear what types of patients with nerve-related cervicobrachial pain (if any) may benefit. Medline, Web of Science, Scopus, PeDro, Cinahl, and Cochrane databases were searched from inception until December 2022. Randomised controlled trials were included if they assessed the effectiveness of NM in nerve-related cervicobrachial pain, and outcome measures were pain intensity and/or disability. Studies were classified according to their inclusion/exclusion criteria as radiculopathy , Wainner cluster , Hall , and Elvey cluster or other . Meta-analyses with subgroup analyses were performed. Risk of bias was assessed using Cochrane Rob2 tool. Twenty-seven studies were included. For pain and disability reduction, NM was found to be more effective than no treatment (pooled pain mean difference [MD] = -2.81, 95% confidence interval [CI] = -3.81 to -1.81; pooled disability standardized mean difference = -1.55, 95% CI = -2.72 to -0.37), increased the effectiveness of standard physiotherapy as an adjuvant when compared with standard physiotherapy alone (pooled pain MD = -1.44, 95% CI = -1.98 to -0.89; pooled disability MD = -11.07, 95% CI = -16.38 to -5.75) but was no more effective than cervical traction (pooled pain MD = -0.33, 95% CI = -1.35 to 0.68; pooled disability MD = -10.09, 95% CI = -21.89 to 1.81). For disability reduction, NM was found to be more effective than exercise (pooled MD = -18.27, 95% CI = -20.29 to -17.44). In most comparisons, there were significant differences in the effectiveness of NM between the subgroups. Neural mobilisations was consistently more effective than all alternative interventions (no treatment, traction, exercise, and standard physiotherapy alone) in 13 studies classified as Wainner cluster . PROSPERO registration: CRD42022376087.

Introduction to a special issue on big data and pain

This special issue comprised 7 articles from leaders in the field that focus on "big pain data", the large datasets and the associated methods for data analysis that are currently emerging in pain research. This collection of articles highlights the power and potential as well as points of caution that multi-disciplinary research utilising big data and their associated methods and interpretations present for pain research.