ArticleAnnals of medicine2025
Predicting acupuncture efficacy for neck pain based on functional connectivity features: a machine learning study.
Article in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Massage Regulates Brain Plasticity in Chronic Sciatic Nerve Compression Injury Rats: A Study Based on Resting-State Functional Magnetic Resonance Imaging.Brain and behavior · 2026Article
- Toward Precision Acupuncture for Pain: Host Genetic Variability, Omics Biomarkers, and Treatment-Response Stratification.Human mutation · 2026Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo explore the mechanisms of acupuncture-induced neck pain relief and identify appropriate candidates using neuroimaging and machine learning techniques.
methodsEighty neck pain patients were included, with clinical data and functional magnetic resonance imaging scans collected pre- and post-treatment. A support vector machine (SVM) model was built using pre-treatment brain functional connectivity to predict acupuncture responsiveness, identifying key features as potential biomarkers for effectiveness. Longitudinal analysis of these features was conducted in responders and non-responders.
resultsThis study enrolled 80 neck pain patients (48 acupuncture responders and 32 non-responders) for SVM model construction and longitudinal analysis of predictive features pre-/post-treatment. The SVM model achieved an accuracy of 0.85 in distinguishing the two groups. A total of 117 functional connectivity edges were identified as predictive features, potential biomarkers for acupuncture responses. Longitudinal analysis showed 6 predictive features altered post-treatment in responders versus 44 in non-responders. After FDR correction, only 3 functional connectivity features in responders negatively correlated with pain VAS scores (
conclusionUsing pre-treatment neuroimaging features to predict acupuncture effectiveness for neck pain shows promise. This approach could aid in developing personalized acupuncture strategies by identifying likely beneficiaries, guiding alternative interventions for non-responders.
trial registrationInternational Traditional Medicine Clinical Trial Registry (registration number: ITMCTR2023000001, protocol version number: V1.0).
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