Multifidus Dysfunction and Chronic Low Back Pain: Systematic Review and Meta-analysis of the Supporting Data for...

Chronic low back pain (CLBP) is a leading cause of disability worldwide. Multifidus muscle dysfunction is increasingly recognized as a distinct contributor to mechanical CLBP. Restorative neurostimulation has emerged as a targeted therapy for this phenotype.

A systematic review and meta-analysis was conducted according to PRISMA guidelines. Databases searched included PubMed, Cochrane, and Web of Science for studies published between January 2013 and September 2025. Eligible studies evaluated implantable restorative neurostimulation in adults with CLBP and multifidus dysfunction. Data extraction included patient demographics, study design, pain, disability, and quality of life outcomes. Risk of bias was assessed using Cochrane and National Institutes of Health tools. The meta-analysis reported pooled mean differences at 1- and 4-year follow-up.

Six studies (N = 650; 546 treated, 104 controls) met inclusion criteria. Restorative neurostimulation resulted in significant improvements in pain (Numerical Rating Scale/visual analog scale), disability (Oswestry Disability Index [ODI]), and quality of life (EQ-5D) at 1 and 4 years. The meta-analysis showed a pooled mean reduction in pain scores of 3.2 (±0.8) at 1 year and 4.1 (±2.1) at 4 years. EQ-5D improved by 0.200 (±0.043) at 1 year and 0.251 (±0.072) at 4 years. Pooled mean ODI improvement was 17.1 at 1 year and 23.0 at 4 years, exceeding minimally clinically important differences at both 1 and 4 years. Mechanistic studies demonstrated reversal of multifidus fibrosis and normalization of muscle spindle structure.

Restorative neurostimulation targeting multifidus dysfunction provides sustained, clinically meaningful improvements in pain, disability, and quality of life for patients with mechanical CLBP. Accurate phenotyping and use of International Classification of Diseases, 10th revision, code M62.85 enable targeted intervention. Further research should focus on comparative effectiveness, cost-effectiveness, and predictive biomarkers to optimize patient selection.