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, 2013, 402180

Network Analysis of Acupuncture Points Used in the Treatment of Low Back Pain

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Network Analysis of Acupuncture Points Used in the Treatment of Low Back Pain

Soon-Ho Lee et al. Evid Based Complement Alternat Med.

Abstract

Background. The appropriate selection of acupoints is fundamental to obtain a therapeutic effect from clinical acupuncture. Objective. Using a network analysis method, we investigated the acupoints that are combined to treat low back pain (LBP). Methods. To analyze the patterns of the combinations of acupoints, we used acupoint information from clinical trials to calculate the modified mutual information (MI) value, integrated these data, and visualized the network. Results. Based on the highest MI values, we found two different types of acupoint pairs used in the treatment of LBP: pairs of distant acupoints and pairs of local acupoints. Using modular analysis, we found that three acupoint modules were applied in the treatment of LBP: local acupoints, distant acupoints along the meridian, and distant acupoints based on the symptom differentiations. Conclusion. Using the modified MI technique, we provide a systematic framework for the acupoint combination network, and reveal how the technique of acupoint combination is used in the treatment of LBP. Application of this knowledge in acupuncture research may help clarify the mechanisms underlying acupuncture treatment at the systems level, bridging the gap between traditional medicine and modern science.

Figures

Figure 1
Figure 1
(a) The MI matrix for acupoint combinations used to treat LBP. The coordinates indicate the order of the main acupoints used for treating LBP. The distance-based mutual information model explains the relationships between all pairs of the 33 acupoints. (b) Binarized MI matrix for the acupoint pairs (threshold value = 0.031). Pairs exceeding the threshold were scored 1 and are shown in red. Pairs below the threshold were scored 0 and these pixels are in blue.
Figure 2
Figure 2
The network model based on module analysis, showing the grouped acupoints. Three modules were identified and are shown in this circular form: Module A (blue nodes), acupoints BL23, BL25, BL24, BL26, BL57, BL32, GV3, GV4, BL52, BL22, BL27, BL31, BL33, and BL34; Module B (orange nodes), acupoints BL60, GB30, BL40, GB34, BL37, ST36, BL62, SI3, and SI6; and Module C (green nodes), acupoints LI4, KI3, LU8, SP9, LR3, KI7, SP3, SP2, HT8, and KI10.
Figure 3
Figure 3
Network models showing degree centrality (a) and betweenness centrality (b). Unlike Figure 2, which groups similar acupoints as modules, this figure separates each acupoint and connects each pair with edges. In both figures, red nodes indicate a high degree of betweenness centrality, green nodes indicate a low value, and yellow nodes indicate an intermediate value.

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