Search

Determining effective traditional Chinese medicine (TCM) treatments for specific disease conditions or particular patient groups is a difficult issue that necessitates investigation because of the complicated personalized manifestations in real-world patients and the individualized combination therapies prescribed in clinical settings. In this study, a multistage analysis method that integrates propensity case matching, complex network analysis, and herb set enrichment analysis was proposed to identify effective herb prescriptions for particular diseases (e.g., insomnia). First, propensity case matching was applied to match clinical cases. Then, core network extraction and herb set enrichment were combined to detect core effective herb prescriptions. Effectiveness-based mutual information was used to detect strong herb-symptom relationships. This method was applied on a TCM clinical data set with 955 patients collected from well-designed observational studies. Results revealed that groups of herb prescriptions with higher effectiveness rates (76.9% vs. 42.8% for matched samples; 94.2% vs. 84.9% for all samples) compared with the original prescriptions were found. Particular patient groups with symptom manifestations were also identified to help investigate the indications of the effective herb prescriptions. [ABSTRACT FROM AUTHOR]

Background: Many previous studies have shown the potential therapeutic effect of acupuncture for allergic rhinitis. Most of these studies, however, were limited by the short duration of observations and lack of sham acupuncture as the control group. Our preliminary experiments showed that the use of a warm needling achieved a much more persistent effect in the treatment of allergic rhinitis (AR) compared with simple acupuncture therapy. Hence, we have designed a multicenter, randomized controlled trial (RCT) in which the first-line medication loratadine will be used as the control group, and the effect of warm needling therapy will be evaluated through long-term observation.Methods/design: The trial is designed as a multicenter, parallel-group, randomized, single-blinded (outcome assessors), non-inferiority trial. A total of 98 patients with persistent AR will be randomly assigned into two groups. Patients in the treatment group will be treated with warm needling at GV14 and acupuncture at EX-HN3, ST2, LI20, EX-HN8, GV23, LU7, LU5 and LI4 three times a week, for a total of 4 weeks. Patients in the control group will be treated with oral loratadine 10 mg/day for 4 weeks. The primary outcome will be the change in the Total Nasal Symptom Score (TNSS) from baseline to that at 6 months after treatment during the follow-up period. The secondary outcomes will include the Total Non-nasal Symptom Score and the Rhinoconjunctivitis Quality of Life Questionnaire, changes in the TNSS from baseline to that at 2 and 4 weeks during treatment, and 3 months after treatment during the follow-up period. Outcomes will be measured at 2 and 4 weeks, and 3 and 6 months after treatment. Any side effects of treatment will be observed and recorded.Discussion: We expect that the study results will provide evidence to determine the effects of warm needling compared with loratadine. Our final goal of the study is to evaluate the difference in the short-term and long-term effects between the two therapeutic methods, especially the long-term effect of warm needling.Trial Registration: ClinicalTrials.gov NCT02339714 . Registered on 14 January 2015. [ABSTRACT FROM AUTHOR]

Traditional Chinese medicine (TCM) is a clinical-based discipline in which real-world clinical practice plays a significant role for both the development of clinical therapy and theoretical research. The large-scale clinical data generated during the daily clinical operations of TCM provide a highly valuable knowledge source for clinical decision making. Secondary analysis of these data would be a vital task for TCM clinical studies before the randomised controlled trials are conducted. In this article, we discuss the challenges and issues, such as structured data curation, data preprocessing and quality, large-scale data management and complex data analysis requirements, in the data processing and analysis of real-world TCM clinical data. Furthermore, we also discuss related state-of-the-art research and solutions in China. We have shown that the clinical data warehouse based on the collection of structured electronic medical record data and clinical terminology would be a promising approach for generating clinical hypotheses and helping the discovery of clinical knowledge from large-scale real-world TCM clinical data. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Background: To systematically analyze differences in atherosclerotic cardiovascular disease (ASCVD) burden between young and older adults. Methods: We estimated the prevalence, mortality, and disability-adjusted life years (DALYs) of ASCVD, including ischemic heart disease (IHD), ischemic stroke (IS), and peripheral artery disease (PAD), in individuals aged 20–54 and > 55 years from 1990–2019, utilizing data from the 2019 Global Burden of Disease Study. The annual percentage changes (EAPCs) for age-specific prevalence, mortality, or DALY rates were calculated to quantify the temporal trends of ASCVD burden. We also analyzed population attribution fractions (PAF) of premature ASCVD mortality and DALYs for different risk factors and compared the burden of extremely premature, premature, and non-premature ASCVD cases based on clinical classifications. Results: From 1990–2019, the global prevalence rates of IHD, IS, and PAD in the 20–54 years age group increased by 20.55% (from 694.74 to 837.49 per 100,000 population), 11.50% (from 439.48 to 490.03 per 100,000 population), and 7.38% (from 384.24 to 412.59 per 100,000 population), respectively. Conversely, the ASCVD prevalence in > 55years age group decreased. Adverse outcome burdens, including mortality and DALYs, varied among ASCVD subtypes. The decrease in the mortality/DALY burden of IHD and IS was lower in the 20–54 years group than in the > 55 years group. For PAD, DALYs among those aged 20–54 increased but decreased among those aged > 55 years. When grouped according to socio-demographic index (SDI) values, lower SDI regions exhibited a higher proportion of young ASCVD burden. The prevalence of young IHD, IS, and PAD in low SDI regions reached 20.70%, 40.05%, and 19.31% in 2019, respectively, compared with 12.14%, 16.32%, and 9.54%, respectively, in high SDI regions. Metabolic risks were the primary contributors to the ASCVD burden in both age groups. Increased susceptibility to ambient particulate matter pollution and inadequate control of high body-mass index and high fasting plasma glucose in young individuals may partially explain the differing temporal trends between young and older individuals. Conclusions: The ASCVD burden in young individuals may become a growing global health concern, especially in areas with lower socioeconomic development levels that require more effective primary prevention strategies. [ABSTRACT FROM AUTHOR]

Background: The purpose of this study was to evaluate left ventricular systolic function in patients with different types of ischemic heart disease using two-dimensional speckle tracking imaging (2D-STI).Methods: We retrospectively studied patients who were admitted to Peking University Third Hospital from January 2011 to December 2017 due to chest tightness and chest pain. Two hundred forty-two patients were divided into control group, CMD group and obstructive CAD group. The main coronary artery stenosis was confirmed by coronary angiography or coronary computed tomography and coronary flow reserve (CFR) in patients was measured by transthoracic Doppler echocardiography. Left ventricular strain and strain rate (SR) measured by 2D-STI. Cardiac structure and function were measured by conventional echocardiography.Results: Conventional echocardiography showed that there was no significant difference in cardiac structure and function among the three groups (P > 0.05). Moreover, the longitudinal strain (LS) of each ventricular wall in CMD group was notably lower than that in control group (P < 0.01). In addition, global longitudinal SR and longitudinal SR in CMD group and obstructive CAD group were obviously lower than those in control group (P < 0.01). GLS, endocardial LS and epicardial LS were negatively correlated with CFR (P < 0.01).Conclusions: Early left ventricular systolic dysfunction was found in patients with CMD and patients with obstructive CAD, with similar degree. CFR is an independent influencing factor of GLS. GLS and stratified LS have certain diagnostic value for CMD. [ABSTRACT FROM AUTHOR]

Background: Syndrome differentiation aims at dividing patients into several types according to their clinical symptoms and signs, which is essential for traditional Chinese medicine (TCM). Several previous works were devoted to employing the classical algorithms to classify the syndrome and achieved delightful results. However, the presence of ambiguous symptoms substantially disturbed the performance of syndrome differentiation, This disturbance is always due to the diversity and complexity of the patients' symptoms.Methods: To alleviate this issue, we proposed an algorithm based on the multilayer perceptron model with an attention mechanism (ATT-MLP). In particular, we first introduced an attention mechanism to assign different weights for different symptoms among the symptomatic features. In this manner, the symptoms of major significance were highlighted and ambiguous symptoms were restrained. Subsequently, those weighted features were further fed into an MLP to predict the syndrome type of AIDS.Results: Experimental results for a real-world AIDS dataset show that our framework achieves significant and consistent improvements compared to other methods. Besides, our model can also capture the key symptoms corresponding to each type of syndrome.Conclusion: In conclusion, our proposed method can learn these intrinsic correlations between symptoms and types of syndromes. Our model is able to learn the core cluster of symptoms for each type of syndrome from limited data, while assisting medical doctors to diagnose patients efficiently. [ABSTRACT FROM AUTHOR]