Predicting acupuncture efficacy for major depressive disorder using baseline clinical variables: A machine learning study.

Acupuncture is a viable treatment option for major depressive disorder (MDD). However, its effectiveness varies among patients. This study aimed to develop a model to predict the efficacy of acupuncture therapy for MDD using machine learning and baseline clinical variables. A total of 124 patients with MDD from five research centers were included in our machine learning study. All patients underwent acupuncture treatment for 6 weeks and the efficacy of the treatment was evaluated using the Hamilton Depression Scale-17 (HAMD-17). The max-relevance and min-redundancy (mRMR) algorithm and Pearson correlation analysis were used for selecting 11 significant features from 26 baseline clinical variables for model training. We compared the performance of five machine learning models, including logistic regression, support vector machine, K-nearest neighbor, random forest, and XgBoost, in predicting the effect of acupuncture in relieving major depression. Among the five models, XgBoost performed the best with an area under the receiver operating characteristic curve (AUC) of 0.835, an accuracy of 0.730, a sensitivity of 0.670, a specificity of 0.774, and an F1 score of 0.751. The key predictive variables identified were anxiety score in the self-rating depression scale (SDS), the traditional Chinese medicine syndrome of deficiency in both heart and spleen, and body mass index (BMI). The study demonstrates that the developed model can help physicians predict the patients who will benefit from acupuncture treatment, which is of positive significance for improving the clinical efficacy of acupuncture on MDD.

Electroacupuncture Improves Depression-Like Behavior by Regulating the Abundance of Lactobacillus and Staphylococci in Mice.

BACKGROUND: Growing evidence suggests that gut microbiota can affect depression-like behavior, and electroacupuncture (EA) can regulate the composition and abundance of gut microbiota. At the same time, not a lot of research has been done on how EA affects gut microbiota to depression-like behavior. The objective of this study was to study the associated mechanisms by which EA exerts antidepressant effects by modulating gut microbiota. METHODS: Twenty-four C57BL/6 male mice were randomly divided into three groups, one group (n = 8) was the normal control group (NC). And the other two groups was chronic unpredictable mild stress for modeling + electroacupuncture group (CUMS + EA) (n = 8) and chronic unpredictable mild stress for modeling group (CUMS) (n = 8). Both CUMS and EA groups were subjected to 28 days of CUMS, but only the EA group received an additional 14 days of EA procedure. Behavior tests were used to determine the antidepressant effect of EA. Sequencing of the 16S ribosomal RNA (rRNA) gene was applied to examine alterations in the intestinal microbiome between groups. RESULTS: The findings were compared to those of the NC group, the sucrose preference rate and the total distance of Open Field Test (OFT) in CUMS group decreased, the abundance of Lactobacillus decreased, while the abundance of staphylococci increased. After the intervention of EA, the sucrose preference index and the total distance of OFT increased, the abundance of Lactobacillus increased, while the abundance of staphylococci decreased. CONCLUSIONS: These findings indicated EA may play an antidepressant effect by adjusting the abundance of Lactobacillus and staphylococci.

Acupuncture for cancer-related insomnia: A systematic review and meta-analysis.

BACKGROUND: Cancer-related insomnia is a highly prevalent complaint in cancer patients. However, there is no meta-analytic synthesis explored the efficacy of acupuncture for cancer-related insomnia among cancer patients undergoing active cancer treatments. OBJECTIVE: This systematic review and meta-analysis were performed to explore the efficacy and safety of acupuncture for insomnia in people diagnosed with cancer. STUDY DESIGN: Systematic review and meta-analysis of existing randomized controlled trials on acupuncture in the treatment of cancer-related insomnia. METHODS: According to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement, we identified and extracted the trials through November 2021 from ten databases and two trials record platforms (Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, PUBMED, Web of Science, PsycINFO, Allied and Complementary Medicine, Cumulative Index to Nursing and Allied Health Literature, China National Knowledge Infrastructure, Wanfang Digital Journals, ClinicalTrials, World Health Organization International Clinical Trials Registry Platform). The quality of the trials was assessed using Jadad score and Risk of Bias (2.0). A meta-analysis was synthesized using the random-effects model if the included studies were in high methodological quality. RESULTS: A total of 690 studies were identified, with 22 were included in the review, and 6 of them were included in the quantitative synthesis. Studies were highly heterogeneous in terms of participant characteristics and study methodologies. Most studies recruited patients diagnosed with a specific cancer type, and breast cancer patients were the subgroup most represented. The qualitative review of available evidence suggested a beneficial efficacy of acupuncture on sleep without serious adverse events in several studies (55%). The meta-analysis revealed that acupuncture produced a significant improvement in the total Pittsburgh Sleep Quality Index (PSQI) score relative to the wait-list control among breast cancer patients undergoing active cancer treatments (MD -1.92, 95% CI -3.25 to -0.59, p = 0.005). Similar improvement of real and sham acupuncture on PSQI score change post-intervention was found (MD: -0.68, 95% CI: -2.44 to 1.07, p = 0.44). Manual acupuncture had similar effective rate as compared to estazolam immediately post-intervention (RR: 0.94, 95% CI: 0.87 to 1.01, p = 0.09), and had significantly better effective rate than estazolam at 1-week post-intervention follow-up (RR: 1.25, 95% CI: 1.10 to 1.43, p = 0.0009). All reported acupuncture related adverse events were mild or moderate in severity. CONCLUSION: Acupuncture has great potential to be used to manage cancer-related insomnia for cancer patients or survivors. More studies with rigorous designs and larger sample size are warranted to verify the efficacy and safety of acupuncture for insomnia among people diagnosed with cancer, in particular among those with clinically significant insomnia. REGISTRATION: PROSPERO (ID: CRD42021285844).