Background. Hyperemesis gravidarum (HG) is a common gastrointestinal disease afflicting gravidas. It usually results in hospital admission in early pregnancy. Objective. Through a meta-analysis, this study intended to explore acupuncture’s clinical efficacy in treating HG. Materials and Methods. A comprehensive search of PubMed, the Cochrane Library, EMBASE, Web of Science, China National Knowledge Infrastructure (CNKI), Chinese Biological Medical (CBM), Wanfang Database, and China Science and Technology Journal (VIP) for published clinical randomized controlled trials (RCTs) of acupuncture for treating HG was conducted from the date of database creation to 20th January 2021. We also searched grey literature in four databases: Chinese Cochrane Center, Chinese Clinical Trial Registry, GreyNet International, and Open Grey from their inception to 20th January 2021. Two authors independently screened the literature, extracted data, and evaluated the quality of the literature with Cochrane Handbook 5.1.0 and Review Manager 5.2 software. Review Manager 5.2 and STATA 12.0 software were applied to analyze data. Heterogeneity analysis was performed by the Cochran Chi-square test and I2 statistic. Egger’s tests together with funnel plots were used to identify publication bias. Results. A total of 16 trials covering 1043 gravidas were included. Compared with the conventional treatment, acupuncture had a significantly higher effective rate (OR: 8.11, 95% CI: 5.29∼12.43; P < 0.00001 ), a higher conversion rate of urine ketone (RR: 1.36, 95% CI: 1.15∼1.60; P = 0.0003 ), an improvement rate of nausea and vomiting (OR: 26.44, 95% CI: 3.54∼197.31; P = 0.001 ), and a relatively higher improvement rate of food intake (RR: 1.17, 95% CI: 1.01∼1.36; P = 0.04 ). Acupuncture also shortened hospitalization time and manifested with a lower pregnancy termination rate and fewer adverse events. Nevertheless, no statistical variation in the improvement of nausea intensity, vomiting episodes, and lassitude symptom, recurrence rate, and serum potassium was observed. Conclusion. Our study suggested that acupuncture was effective in treating HG. However, as the potential inferior quality and underlying publication bias were found in the included studies, there is a need for more superior-quality RCTs to examine their effectiveness and safety. PROSPERO registration number: CRD42021232187.
Background Nowadays, intelligent medicine is gaining widespread attention, and great progress has been made in Western medicine with the help of artificial intelligence to assist in decision making. Compared with Western medicine, traditional Chinese medicine (TCM) involves selecting the specific treatment method, prescription, and medication based on the dialectical results of each patient’s symptoms. For this reason, the development of a TCM-assisted decision-making system has lagged. Treatment based on syndrome differentiation is the core of TCM treatment; TCM doctors can dialectically classify diseases according to patients’ symptoms and optimize treatment in time. Therefore, the essence of a TCM-assisted decision-making system is a TCM intelligent, dialectical algorithm. Symptoms stored in electronic medical records are mostly associated with patients’ diseases; however, symptoms of TCM are mostly subjectively identified. In general electronic medical records, there are many missing values. TCM medical records, in which symptoms tend to cause high-dimensional sparse data, reduce algorithm accuracy. Objective This study aims to construct an algorithm model compatible for the multidimensional, highly sparse, and multiclassification task of TCM syndrome differentiation, so that it can be effectively applied to the intelligent dialectic of different diseases. Methods The relevant terms in electronic medical records were standardized with respect to symptoms and evidence-based criteria of TCM. We structuralized case data based on the classification of different symptoms and physical signs according to the 4 diagnostic examinations in TCM diagnosis. A novel cross-feature generation by convolution neural network model performed evidence-based recommendations based on the input embedded, structured medical record data. Results The data set included 5273 real dysmenorrhea cases from the Sichuan TCM big data management platform and the Chinese literature database, which were embedded into 60 fields after being structured and standardized. The training set and test set were randomly constructed in a ratio of 3:1. For the classification of different syndrome types, compared with 6 traditional, intelligent dialectical models and 3 click-through-rate models, the new model showed a good generalization ability and good classification effect. The comprehensive accuracy rate reached 96.21%. Conclusions The main contribution of this study is the construction of a new intelligent dialectical model combining the characteristics of TCM by treating intelligent dialectics as a high-dimensional sparse vector classification task. Owing to the standardization of the input symptoms, all the common symptoms of TCM are covered, and the model can differentiate the symptoms with a variety of missing values. Therefore, with the continuous improvement of disease data sets, this model has the potential to be applied to the dialectical classification of different diseases in TCM.
Background: Oral ulcers (OU) is a common oral mucosal disease manifested with obvious pain; in some studies, the efficacy of acupuncture in OU has been confirmed, but the systematic reviews and meta-analyses for them are lacking. Our aim is to evaluate the efficacy and safety of acupuncture in the treatment of OU. Methods: Relevant randomized controlled trials (RCTs), quasi RCTs and non-RCTs will be identified by systematic searching from the following electronic databases: PubMed, Embase, the Cochrane Library, Chinese Biomedical Literature Database, China National Knowledge Infrastructure, China Science and Technology Journal database, and Wanfang Data (since inception of the databases to present). In addition, ongoing trials will be retrieved from the Chinese Clinical Trial Register, World Health Organization International Clinical Trials Registry Platform, Clinical Trials, and The Clinical Trials Register. Grey literature will be also taken into consideration, including academic dissertation, minutes of the meeting from Chinese Biomedical Literature Database, China National Knowledge Infrastructure, China Science and Technology Journal database, and Wanfang Data. There are no language restrictions. Results: Ethical approval is not required because this study is based on published papers. After peer-review, the study will be disseminated in scientific journals and conferences. Conclusion: This systematic review will provide evidence for the efficacy and safety of acupuncture for Oral ulcers. Trial registration number: CRD42020144911.
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