Combination of Acupoints in Treating Patients with Chronic Obstructive Pulmonary Disease: An Apriori Algorithm-Based Association Rule Analysis

Transcriptomic Insights into Different Stimulation Intensity of Electroacupuncture in Treating COPD in Rat Models

Background

Electroacupuncture (EA), with varying stimulation intensities, has demonstrated therapeutic potentials in both animal and clinical studies for the treatment of chronic obstructive pulmonary disease (COPD). However, a comprehensive investigation of the intensity-related effects, particularly 1mA and 3mA of EA, and the underlying mechanisms remains lacking.

Methods

A COPD rat model was established by prolonged exposure to cigarette smoke and intermittent intratracheal instillation of lipopolysaccharide. EA treatment was administered at acupoints BL13 (Feishu) and ST36 (Zusanli), 20 minutes daily for 2 weeks, with intensities of 1mA and 3mA. EA effectiveness was evaluated by pulmonary function, histopathological change, serum level of inflammatory cytokines, and level of oxidative stress markers in serum and lung tissues. Transcriptome profiling and weighted gene co-expression network analysis (WGCNA) were performed to reveal gene expression patterns and identify hub genes. Real-time quantitative PCR (RT-qPCR) and Western blot (WB) were performed to detect the mRNA and protein expression levels, respectively.

Results

EA at both 1mA and 3mA exerted differing therapeutic effects by improving lung function and reducing inflammation and oxidative stress in COPD rats. Transcriptome analysis revealed distinct expression patterns between the two groups, functionally corresponding to shared and intensity-specific (1mA and 3mA) enriched pathways. Eight candidate genes were identified, including Aqp9, Trem1, Mrc1, and Gpnmb that were downregulated by EA and upregulated in COPD. Notably, Msr1 and Slc26a4 exclusively downregulated in EA-1mA, while Pde3a and Bmp6 upregulated solely in EA-3mA. WGCNA constructed 5 key modules and elucidated the module-trait relationship, with the aforementioned 8 genes being highlighted. Additionally, their mRNA and protein levels were validated by RT-qPCR and WB.

Conclusion

Our results demonstrated that 1mA and 3mA intensities induce distinct gene expression patterns at the transcriptional level, associated with shared and 1mA vs 3mA-specific enriched pathways. Genes Mrc1, Gpnmb, Trem1, and Aqp9 emerge as promising targets, and further studies are needed to elucidate their functional consequences in COPD.

Chinese herbal compound for multidrug-resistant or extensively drug-resistant bacterial pneumonia: a meta-analysis and trial sequential analysis with association rule mining to identify core herb combinations

Purpose: Antibiotic-resistant bacterial pneumonia poses a significant therapeutic challenge. In China, Chinese herbal compound (CHC) is commonly used to treat bacterial pneumonia. We aimed to evaluate the efficacy and safety of CHC and identify core herb combinations for the treatment of multidrug-resistant or extensively drug-resistant bacterial pneumonia. Methods: Stata 16 and TSA 0.9.5.10 beta software were used for meta-analysis and trial sequential analysis (TSA), respectively. Exploring the sources of heterogeneity through meta-regression and subgroup analysis. Results: Thirty-eight studies involving 2890 patients were included in the analyses. Meta-analysis indicated that CHC combined with antibiotics improved the response rate (RR = 1.24; 95% CI: 1.19-1.28; p < 0.0001) and microbiological eradication (RR = 1.41; 95% CI: 1.27-1.57; p < 0.0001), lowered the white blood cell count (MD = -2.09; 95% CI: -2.65 to -1.53; p < 0.0001), procalcitonin levels (MD = -0.49; 95% CI: -0.59 to -0.40; p < 0.0001), C-reactive protein levels (MD = -11.80; 95% CI: -15.22 to -8.39; p < 0.0001), Clinical Pulmonary Infection Scores (CPIS) (MD = -1.97; 95% CI: -2.68 to -1.26; p < 0.0001), and Acute Physiology and Chronic Health Evaluation (APACHE)-II score (MD = -4.08; 95% CI: -5.16 to -3.00; p < 0.0001), shortened the length of hospitalization (MD = -4.79; 95% CI: -6.18 to -3.40; p < 0.0001), and reduced the number of adverse events. TSA indicated that the response rate and microbiological eradication results were robust. Moreover, Scutellaria baicalensis Georgi, Fritillaria thunbergii Miq, Lonicera japonica Thunb, and Glycyrrhiza uralensis Fisch were identified as core CHC prescription herbs. Conclusion: Compared with antibiotic treatment, CHC + antibiotic treatment was superior in improving response rate, microbiological eradication, inflammatory response, CPIS, and APACHE-II score and shortening the length of hospitalization. Association rule analysis identified four core herbs as promising candidates for treating antibiotic-resistant bacterial pneumonia. However, large-scale clinical studies are still required. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023410587.

Data-mining-based of ancient traditional Chinese medicine records from 475 BC to 1949 to potentially treat COVID-19

Traditional Chinese Medicine (TCM) plays a role in preventing and treating COVID-19 in China. Based on the manifestations and symptoms of COVID-19, our study used the data mining method to summarize related therapeutic experience left by predecessors who used TCM to treat epidemics in their eras. Initially, we collected abundant medical records with similar manifestations of COVID-19 in Chinese ancient times. The key words including wen (), yi (), li (), and zhang () were searched in ZhongyiZhiku (https://www.zk120.com/) from Warring States Period (475 BC-221 BC) to the Republic of China era (1912-1949) to locate ancient medical records according to inclusion criteria and exclusion criteria. Moreover, COVID-19-related manifestations and corresponding medications in those records were categorized. Eventually, Traditional Chinese Medicine Inheritance Support System version 2.5 was used to build a medical record database of TCM treating COVID-19. Our study collected 263 epidemic medical records comprising COVID-19 related manifestations and found that Chinese Materia Medica (CMM) combinations excavated from ancient medical records included Ren Shen Bai Du San, Wu Ling San, Xiao Chai Hu Tang, Da Cheng Qi Tang, Da Chai Hu Tang, Ling Gui Zhu Gan Tang, and Qing Wen Bai Du Yin. The recurrent CMMs with a high frequency for treating COVID-19 manifestations were Scutellariae Radix (Huang Qin), Paeoniae Alba Radix (Bai Shao), Poria (Fu Ling), and Bupleuri Radix (Chai Hu). Our study suggests that TCM might offer new therapeutic strategies for COVID-19.

Withdrawn: A data-mining based analysis of traditional Chinese medicine in diagnosing and treating COVID-19

Yongshen Fan, Ting Zhao, Yaxue Han, Zi Yang, Shan Fang, Mengqing Zhang, Zhijun Xie, A data-mining based analysis of traditional Chinese medicine in diagnosing and treating COVID-19, The Anatomical Record: Advances in Integrative Anatomy and Evolutionary Biology 2021, (https://doi.org/10.1002/ar.24677). The above article, published online on 24 June 2021 in Wiley Online Library (wileyonlinelibrary.com), has been withdrawn by agreement between the journal Editor-in-Chief, Heather F. Smith, Ph.D., the American Association for Anatomy, and Wiley Periodicals LLC. The authors have been notified of the decision to withdraw the article. The decision is based on concerns raised by a third party. The Editor-in-Chief considers the conclusions of the paper compromised and has initiated an investigation.

Patterns and Determinants of Multimorbidity in Older Adults: Study in Health-Ecological Perspective

(1) Background: Multimorbidity has become one of the key issues in the public health sector. This study aims to explore the patterns and health-ecological factors of multimorbidity in China to propose policy recommendations for the management of chronic diseases in the elderly. (2) Methods: A multi-stage random sampling method was used to conduct a questionnaire survey on 3637 older adults aged 60 and older in Shanxi, China. Association rule mining analysis (ARM) and network analysis were applied to analyze the patterns of multimorbidity. The health-ecological model was adopted to explore the potential associated factors of multimorbidity in a multidimensional perspective. A hierarchical multiple logistic model was employed to investigate the association strengths reflected by adjusted odds ratios and 95% confidence. (3) Results: Multimorbidity occurred in 20.95% of the respondents. The graph of network analysis showed that there were 6 combinations of chronic diseases with strong association strengths and 14 with moderate association strengths. The results of the ARM were similar to the network analysis; six dyadic chronic disease combinations and six triadic ones were obtained. Hierarchical multiple logistic regression indicated that innate personal traits (age, history of genetics, and body mass index), behavioral lifestyle (physical activity levels and medication adherence), interpersonal network (marital status), and socioeconomic status (educational level) were the common predictors of multimorbidity for older adults, among which, having no family history was found to be a relative determinant as a protective factor for multimorbidity after controlling the other covariates. (4) Conclusions: multimorbidity was prevalent in older adults and most disease combinations are associated with hypertension, followed by diabetes. This shows that diabetes and hypertension have a high prevalence among older adults and have a wide range of associations with other chronic diseases. Exploring the patterns and associated factors of multimorbidity will help the country prevent complications and avoid the unnecessary use of the health service, adopting an integrated approach to managing multimorbidity rather than an individual disease-specific approach and implementing different strategies according to the location of residence.

Analysis of prescription medication rules of traditional Chinese medicine for bradyarrhythmia treatment based on data mining

BACKGROUND

Multiple studies have revealed that Traditional Chinese Medicine (TCM) prescriptions can provide protective effect on the cardiovascular system, increase the heart rate and relieve the symptoms of patients with bradyarrhythmia. In China, the TCM treatment of bradyarrhythmia is very common, which is also an effective complementary therapy. In order to further understand the application of Chinese medicines in bradyarrhythmia, we analyzed the medication rules of TCM prescriptions for bradyarrhythmia by data mining methods based on previous clinical studies.

METHODS

We searched studies reporting the clinical effect of TCM on bradyarrhythmia in the PubMed and Chinese databases China National Knowledge Infrastructure database, and estimated publication bias by risk of bias tools ROB 2. Descriptive analysis, hierarchical clustering analysis and association rule analysis based on Apriori algorithm were carried out by Microsoft Excel, SPSS Modeler, SPSS Statistics and Rstidio, respectively. Association rules, co-occurrence and clustering among Chinese medicines were found.

RESULTS

A total of 48 studies were included in our study. Among the total 99 kinds of Chinese medicines, 22 high-frequency herbs were included. Four new prescriptions were obtained by hierarchical cluster analysis. 81 association rules were found based on association rule analysis, and a core prescription was intuitively based on the grouping matrix of the top 15 association rules (based on confidence level), of which Guizhi, Zhigancao, Wuweizi, Chuanxiong, Danshen, Danggui, Huangqi, Maidong, Dangshen, Rougui were the most strongly correlated herbs and in the core position.

CONCLUSION

In this study, data mining strategy was applied to explore the TCM prescription for the treatment of bradyarrhythmia, and high-frequency herbs and core prescription were found. The core prescription was in line with the treatment ideas of TCM for bradyarrhythmia, which could intervene the disease from different aspects and adjust the patient's Qi, blood, Yin and Yang, so as to achieve the purpose of treatment.

An Apriori Algorithm-Based Association Analysis of Analgesic Drugs in Chinese Medicine Prescriptions Recorded From Patients With Rheumatoid Arthritis Pain

Chronic pain, a common symptom of people with rheumatoid arthritis, usually behaves as persistent polyarthralgia pain and causes serious damage to patients' physical and mental health. Opioid analgesics can lead to a series of side effects like drug tolerance and addiction. Thus, seeking an alternative therapy and screening out the corresponding analgesic drugs is the key to solving the current dilemma. Traditional Chinese Medicine (TCM) therapy has been recognized internationally for its unique guiding theory and definite curative effect. In this study, we used the Apriori Algorithm to screen out potential analgesics from 311 cases that were treated with compounded medication prescription and collected from “Second Affiliated Hospital of Zhejiang Chinese Medical University” in Hangzhou, China. Data on 18 kinds of clinical symptoms and 16 kinds of Chinese herbs were extracted based on this data mining. We also found 17 association rules and screened out four potential analgesic drugs—“Jinyinhua,” “Wugong,” “Yiyiren,” and “Qingfengteng,” which were promised to help in the clinical treatment. Besides, combined with System Cluster Analysis, we provided several different herbal combinations for clinical references.

Efficacy of Acupuncture on Quality of Life, Functional Performance, Dyspnea, and Pulmonary Function in Patients with Chronic Obstructive Pulmonary Disease: Protocol for a Randomized Clinical Trial

Chronic obstructive pulmonary disease (COPD) is a respiratory disease characterized by the presence of chronic airflow obstruction. Previous studies have evaluated the effect of acupuncture treatment (AT) in patients with COPD. Nevertheless, these studies show a great deal of heterogeneity in treatment protocols, having sample sizes that are too small to estimate and clarify effect size and heterogeneity in patients’ baseline. The aim of this study is to evaluate the effectiveness of acupuncture on quality of life, functional performance, dyspnea, and pulmonary function in patients with COPD. As such, patients will go through the following three phases: Phase I–pretreatment: period of subject selection and inclusion in the protocol, with an interview and performance of exams and tests as follows: Mini-Cog, dual-energy X-ray absorptiometry, spirometry, the Patient-Generated Index, Saint George’s Respiratory Questionnaire, the six-minute walk test, the London Chest Activity of Daily Living, and the COPD Assessment Test. Phase II–8 weeks of treatment, with AT 3 times a week, with two parallel groups: Group I–with 50 subjects–AT according to the recommended technical standards; Group II–with 50 subjects–Control, without acupuncture. Phase III–Continuation of AT for 8 weeks, maintaining the subjects in the previously allocated groups and following the same methodology.

Multidimensional Heterogeneous Network Link Adaptation Based on Mobile Environment

With the development of communication technology, train control operation system develops gradually, which significantly improves the reliability and efficiency of train operation. The current mobile Internet has gradually highlighted the many limitations of the mobile Internet in the high-speed mobile environment, which seriously deteriorate the service quality and user experience, and cause a waste of resources. In order to meet the real-time requirements of network communication resource scheduling in the mobile environment, aiming at the multidimensional dynamic adaptation framework constructed in a mobile environment, a service and network adaptation mechanism based on link failure state prediction is proposed in the paper. First, cross-layer theoretical analysis and actual data analysis are combined to construct a wireless link failure probability model. Then, reliable transmission requirements and transmission overhead are applied to optimize goals. Finally, simulation experiments are carried out according to the railway network data to evaluate the E-GCF adaptation algorithm. The experiment results show that compared with the current mainstream algorithms, the prediction accuracy of this adaptation algorithm is improved by 25%. The execution time of the algorithm is reduced by 9.6 seconds and the successful submission rate is as high as 99.99%. The advantages of the algorithm are significantly superior other algorithms. It proves that the research method of this paper can effectively improve the satisfaction rate and utility value of reliable transmission, as well as enhance the throughput performance. It solves the adaptation problems of frequent switching and low utilization of heterogeneous networks in a mobile environment, which contributes to the high-quality communication service of mobile network.

Combined Acupoints for the Treatment of Patients with Obesity: An Association Rule Analysis

Obesity is a prevalent metabolic disease that increases the risk of other diseases, such as hypertension, diabetes, hyperlipidemia, cardiovascular disease, and certain cancers. A meta-analysis of 11 randomized sham-controlled trials indicates that acupuncture had adjuvant benefits in improving simple obesity, and previous studies have reported that acupoint combinations were more useful than single-acupoint therapy. The Apriori algorithm, a data mining-based analysis that finds potential correlations in datasets, is broadly applied in medicine and business. This study, based on the Apriori algorithm-based association rule analysis, found the association rules of acupoints among 11 randomized controlled trials (RCTs). There were 23 acupoints extracted from 11 RCTs. We used Python to calculate the association between acupoints and disease. We found the top 10 frequency acupoints were Extra12, TF4, LI4, LI11, ST25, ST36, ST44, CO4, CO18, and CO1. We investigated the 1118 association rule and found that {LI4, ST36} ≥ {ST44}, {LI4, ST44} ≥ {ST36}, and {ST36, ST44} ≥ {LI4} were the most associated rules in the data. Acupoints, including LI4, ST36, and ST44, are the core acupoint combinations in the treatment of simple obesity.

East Asian Herbal Medicine to Reduce Primary Pain and Adverse Events in Cancer Patients : A Systematic Review and Meta-Analysis With Association Rule Mining to Identify Core Herb Combination

Objective: Cancer pain is an important factor in cancer management that affects a patient’s quality of life and survival-related outcomes. The aim of this review was to systematically evaluate the efficacy and safety of oral administration of East Asian herbal medicine (EAHM) for primary cancer pain and to explore core herb patterns based on the collected data.

Methods: A comprehensive literature search was conducted in 11 electronic databases, namely, PubMed, Cochrane Library, Cumulative Index to Nursing & Allied Health Literature, EMBASE, Korean Studies Information Service System, Research Information Service System, Oriental Medicine Advanced Searching Integrated System, Korea Citation Index, Chinese National Knowledge Infrastructure Database (CNKI), Wanfang Data, and CiNii for randomized controlled trials from their inception until August 19, 2021. Statistical analysis was performed in R version 4.1.1 and R studio program using the default settings of the meta-package. When heterogeneity in studies was detected, the cause was identified through meta-regression and subgroup analysis. Methodological quality was independently assessed using the revised tool for risk of bias in randomized trials (Rob 2.0).

Results: A total of 38 trials with 3,434 cancer pain patients met the selection criteria. Meta-analysis favored EAHM-combined conventional medicine on response rate (risk ratio: 1.06; 95% CI: 1.04 to 1.09, p < 0.0001), continuous pain intensity (standardized mean difference: −1.74; 95% CI: −2.17 to −1.30, p < 0.0001), duration of pain relief (standardized mean difference: 0.96, 95% CI: 0.69 to 1.22, p < 0.0001), performance status (weighted mean difference: 10.71; 95% CI: 4.89 to 16.53, p = 0.0003), and opioid usage (weighted mean difference: −20.66 mg/day; 95% CI: −30.22 to −11.10, p < 0.0001). No significant difference was observed between EAHM and conventional medicine on response rate and other outcomes. Patients treated with EAHM had significantly reduced adverse event (AE) incidence rates. In addition, based on the ingredients of herb data in this meta-analysis, four combinations of herb pairs, which were frequently used together for cancer pain, were derived.

Conclusion: EAHM monotherapy can decrease adverse events associated with pain management in cancer patients. Additionally, EAHM-combined conventional medicine therapy may be beneficial for patients with cancer pain in increasing the response rate, relieving pain intensity, improving pain-related performance status, and regulating opioid usage. However, the efficacy and safety of EAHM monotherapy are difficult to conclude due to the lack of methodological quality and quantity of studies. More well-designed, multicenter, double-blind, and placebo-controlled randomized clinical trials are needed in the future. In terms of the core herb combination patterns derived from the present review, four combinations of herb pairs might be promising for cancer pain because they have been often distinctly used for cancer patients in East Asia. Thus, they are considered to be worth a follow-up study to elucidate their actions and effects.

Systematic Review Registration:https://www.crd.york.ac.uk/prospero/, identifier CRD42021265804

Oral Administration of East Asian Herbal Medicine for Peripheral Neuropathy: A Systematic Review and Meta-Analysis with Association Rule Analysis to Identify Core Herb Combinations

This review aimed to comprehensively assess the efficacy and safety of oral East Asian herbal medicine (EAHM) for overall peripheral neuropathy (PN). In addition, an Apriori algorithm-based association rule analysis was performed to identify the core herb combination, thereby further generating useful hypotheses for subsequent drug discovery. A total of 10 databases were searched electronically from inception to July 2021. Randomized clinical trials (RCTs) comparing EAHM with conventional analgesic medication or usual care for managing PN were included. The RCT quality was appraised using RoB 2.0, and the random effects model was used to calculate the effect sizes of the included RCTs. The overall quality of evidence was evaluated according to the Grading of Recommendations Assessment, Development, and Evaluation. By analyzing the constituent herb data, the potential association rules of core herb combinations were explored. A total of 67 RCTs involving 5753 patients were included in this systematic review. In a meta-analysis, EAHM monotherapy and combined EAHM and western medicine therapy demonstrated substantially improved sensory nerve conduction velocity, motor nerve conduction velocity, and response rate. Moreover, EAHM significantly improved the incidence rate, pain intensity, Toronto clinical scoring system, and Michigan diabetic neuropathy score. The evidence grade was moderate to low due to the substantial heterogeneity among the studies. Nine association rules were identified by performing the association rule analysis on the extraction data of 156 EAHM herbs. Therefore, the constituents of the herb combinations with consistent association rules were Astragali Radix, Cinnamomi Ramulus, and Spatholobi Calulis. This meta-analysis supports the hypothesis that EAHM monotherapy and combined therapy may be beneficial for PN patients, and follow-up research should be conducted to confirm the precise action target of the core herb.

East Asian herbal medicine for cancer pain: A protocol for systematic review and meta-analysis with using association rule analysis to identify core herb pattern

BACKGROUND

Cancer pain is an important factor in cancer management that affects a patient's quality of life and survival-related outcomes. The aim of this review is to systematically evaluate the efficacy and safety of oral administration East Asian herbal medicine (EAHM) for primary cancer pain, and to explore core herb patterns based on collected data.

METHODS

A comprehensive literature search will be conducted in 10 electronic databases including PubMed, Cochrane Library, Cumulative Index to Nursing & Allied Health Literature, EMBASE, Korean Studies Information Service System, Research Information Service System Oriental Medicine Advanced Searching Integrated System, Korea Citation Index, Chinese National Knowledge Infrastructure Database (CNKI), CiNii for randomized controlled trials from their inception until August 19, 2021. Statistical analysis will be performed in the software R version 4.1.1. and R studio program using the default settings of the 'meta' package. When heterogeneity in studies is detected, the cause will be identified through meta regression and subgroup analysis. Methodological quality will be assessed independently using the revised tool for risk of bias in randomized trials (Rob 2.0).

RESULTS

This study will provide more comprehensive and specific evidence of EAHM for cancer pain management.

CONCLUSIONS

Based on the results of this review, it is expected that the efficacy and safety of East Asian herbal medicine for cancer pain may be confirmed. In addition, it will be possible to derivation of a core herb pattern related to this research topic through additional association rule mining analysis.

Oral administration of East Asian herbal medicine for peripheral neuropathy: A protocol for systematic review and meta-analysis with using association rule analysis to identify core herb pattern

BACKGROUND

Peripheral neuropathy (PN) is one of the most common medical problems encountered. Since the pathophysiology and symptom manifestation characteristics of PN are very diverse, it is difficult to provide an appropriate treatment. East Asian herbal medicine (EAHM) has long contributed to the treatment of neurological and pain disorders. The goal of this systematic review is to measure the efficacy and safety of EAHM for PN and to identify core herb patterns. In order to derive a more conservative result, a random effect model will be applied regardless of the significance of heterogeneity.

METHODS

We will search 10 databases to identify suitable studies. There will be no restrictions regarding language or publication date. Primary outcomes will be nerve conduction velocity and response rate. Secondary outcomes will be any objective tool that can measure the efficacy of EAHM, and adverse events will be included. We will perform a meta-analysis of trials with the same intervention and outcome with comparator in a similar population. Meanwhile, in order to explore significant potential correlation in herb preparation, association rule analysis based on the Apriori algorithm will be performed on the collected composition data of herbal medicines.

RESULTS

This study will provide scientific evidence for the treatment of EAHM for PN.

CONCLUSIONS

Based on the results of this review, it is expected that the efficacy and safety of EAHM for PN can be confirmed. In addition, through additional analysis using data mining techniques, it will be possible to present a core herb pattern related to this research topic.

Urban-Rural Differences in Patterns and Associated Factors of Multimorbidity Among Older Adults in China: A Cross-Sectional Study Based on Apriori Algorithm and Multinomial Logistic Regression

Introduction: Multimorbidity has become one of the key issues in the public health sector. This study aimed to explore the urban–rural differences in patterns and associated factors of multimorbidity in China and to provide scientific reference for the development of health management strategies to reduce health inequality between urban and rural areas.

Methods: A cross-sectional study, which used a multi-stage random sampling method, was conducted effectively among 3,250 participants in the Shanxi province of China. The chi-square test was used to compare the prevalence of chronic diseases among older adults with different demographic characteristics. The Apriori algorithm and multinomial logistic regression were used to explore the patterns and associated factors of multimorbidity among older adults, respectively.

Results: The findings showed that 30.3% of older adults reported multimorbidity, with significantly higher proportions in rural areas. Among urban older adults, 10 binary chronic disease combinations with strong association strength were obtained. In addition, 11 binary chronic disease combinations and three ternary chronic disease combinations with strong association strength were obtained among rural older adults. In rural and urban areas, there is a large gap in patterns and factors associated with multimorbidity.

Conclusions: Multimorbidity was prevalent among older adults, which patterns mainly consisted of two or three chronic diseases. The patterns and associated factors of multimorbidity varied from urban to rural regions. Expanding the study of urban–rural differences in multimorbidity will help the country formulate more reasonable public health policies to maximize the benefits of medical services for all.

Acupuncture Point Stimulation Treatments Combined With Conventional Treatment in Chronic Obstructive Pulmonary Disease: A Systematic Review and Network Meta-Analysis

Background: Chronic obstructive pulmonary disease (COPD), which is a disease characterized by dyspnea, cough, and respiratory symptoms, leading to impaired health-related quality of life (HRQL) and exercise capacity, is highly prevalent worldwide. Some studies demonstrated that acupuncture point stimulation treatments (APSTs) are effective and safe in treating patients with COPD. The aim of this systematic review and network meta-analysis is to analyze the effects on HRQL and FEV1% predicted of diverse APSTs in treating patients with COPD.

Materials and Methods: We searched seven electronic databases. Randomized controlled trials (RCTs) with stable COPD patients comparing APSTs and conventional treatment (Tx) were included. The primary outcome was HRQL measured by COPD Assessment Test or St. George's Respiratory Questionnaire. The secondary outcome was FEV1% predicted. We performed random effect network meta-analysis using a consistency model.

Results: This network meta-analysis analyzed 21 RCTs with 1,577 stable COPD participants. In comparison with Tx, acupressure massage (AM) + Tx [−5.11; 95% confidence interval (CI), −6.65 to −3.57] was the most effective intervention in improving HRQL, followed by moxibustion (Mx) + Tx (−2.86; 95% CI, −3.86 to −1.86). Moreover, in comparison with Tx, Mx + Tx (7.79; 95% CI, 2.16 to 13.42) was the most effective intervention in improving FEV1% predicted, followed by acupuncture (A) + Tx (5.79; 95% CI, 2.90 to 8.68).

Conclusions: Combined interventions (APSTs + Tx) are more effective than single intervention in improving both HRQL and FEV1% predicted. AM, Mx, and A can be considered effective non-pharmacological complementary interventions in treating patients with COPD under Tx.

An Apriori Algorithm-Based Association Rule Analysis to Identify Acupoint Combinations for Treating Diabetic Gastroparesis

We explored the potential association rules within acupoints in treating diabetic gastroparesis (DGP) using Apriori algorithm complemented with another partition-based algorithm, a frequent pattern growth algorithm. Apriori algorithm is a data mining-based analysis that is widely applied in various fields, such as business and medicine, to mine frequent patterns in datasets. To search for effective acupoint combinations in the treatment of DGP, we implemented Apriori algorithm to investigate the association rules of acupoints among 17 randomized controlled trials (RCTs). The acupoints were extracted from the 17 included RCTs. In total, 29 distinct acupoints were observed in the RCTs. The top 10 frequently selected acupoints were CV12, ST36, PC6, ST25, BL21, BL20, BL23, SP6, BL18, and ST21. The frequency pattern of acupoints achieved by using a frequent pattern growth algorithm also confirms the result. The results showed that the most associated rules were {BL23, BL18} ≥ {SP6}, {BL20, BL18} ≥ {PC6}, {PC6, BL18} ≥ {BL20}, and {SP6, BL18} ≥ {BL23} in the database. Acupoints, including BL23, BL18, SP6, BL20, and PC6, can be deemed as core elements of acupoint combinations for treating DGP.

Acupoints for Tension-Type Headache: A Literature Study Based on Data Mining Technology

Objectives

This study aimed to explore the characteristics and principles of acupoints, which were applied for treating tension-type headache (TTH).

Methods

Four databases were searched for the literature studies of treating TTH with acupuncture and moxibustion up to September 1, 2020. Titles, journals, authors, key words, interventions, main acupoints, and outcomes of the included literature studies were extracted and inputted into the self-established Data Excavation Platform of Acupoint Specificity for analysis.

Results

In total, 128 papers containing 137 prescriptions, 89 meridian acupoints, and 7 extraordinary acupoints of treating TTH with acupuncture and moxibustion were included. The total frequency of acupoints' application was 763 times. Fengchi (GB20), Baihui (GV20), Taiyang (EX-HN5), Hegu (LI4), and Taichong (LR3) were used most frequently. The acupoints in Yang meridians were utilized more than those in Yin meridians (66.1% vs. 17.8%), and the acupoints in the Gallbladder Meridian of Foot Shaoyang were applied most commonly. 59.9% (457/763) of the applied acupoints were on the head, face, and neck, and 31.7% (242/763) were on the four limbs. Additionally, the proportion of specific acupoints' application was 78.2% (597/763).

Conclusions

The prescription of Fengchi (GB20), Baihui (GV20), Taiyang (EX-HN5), Hegu (LI4), and Taichong (LR3) might be relatively reasonable in clinical practices of treating TTH with acupuncture, which should be verified in further studies.