Traditional Chinese Medicine Syndrome Differentiation Research Articles

Efficacy and safety of Danlou tablets in the treatment of stable angina pectoris with intermingled phlegm and blood stasis syndrome in coronary heart disease: a multicenter randomized controlled study

ObjectivesIn this study, we assessed the clinical efficacy and safety of Danlou tablets in the treatment of stable angina pectoris (SAP) with intermingled phlegm and blood stasis (IPBS), to provide high-quality evidence-based medical evidence for the prevention and treatment of coronary heart disease.MethodsIn this multicenter randomized controlled study, 304 patients diagnosed with stable angina pectoris with IPBS enrolled from 12 national traditional Chinese medicine (TCM) clinical research centers in China were randomly assigned to the treatment group and the control group at a ratio of 1:1. Each group was divided into four subgroups based on the results of TCM syndrome differentiation: IPBS, IPBS combined with qi deficiency, IPBS combined with qi stagnation, and IPBS combined with toxin accumulation. The control group was treated with routine Western medicine. In addition to routine Western medicine treatment, the treatment group (the IPBS group) was treated with Danlou tablets or Danlou tablets supplemented by interventional therapies based on the results of traditional Chinese medicine differentiation. The frequency of angina attacks per week was the main efficacy evaluation indicator and the secondary efficacy evaluation indicators included angina symptom score, Seattle Angina Questionnaire, an electrocardiogram (ECG) efficacy evaluation, a cardiac Doppler two-dimensional ultrasound, an electrocardiogram treadmill exercise test, blood lipids, blood glucose, a coagulation function test, hemorheology indicators, homocysteine, C-reactive protein (CRP) or high sensitivity-CRP, TCM syndromes (syndrome score, tongue, pulse), and long-term prognosis (endpoint outcome, cardiovascular events).ResultsThere were 300 cases in the full analysis set (FAS), 266 in the per-protocol set (PPS), and 300 in the safety set. Regarding the main efficacy indicator, after treatment, the reduction in the frequency of weekly angina attacks in the treatment group was significantly greater than that in the control group (P < 0.05). The results of the FAS and PPS were consistent. Regarding the secondary efficacy evaluation indicators, the angina symptom, TCM syndrome, ECG evaluation, Seattle Angina Pectoris Questionnaire, and 36-item Health Status Survey Summary Form scores of the treatment group were significantly higher than the control group (P < 0.05) and the homocysteine levels of the treatment group were significantly reduced (P < 0.05). The results of the FAS and PPS were consistent. In the PPS, the triglyceride levels in the treatment group were significantly lower than those in the control group after treatment (P < 0.05). The activated partial thromboplastin time in the treatment group decreased significantly (P < 0.05). There was no statistically significant difference in the safety indicators and incidence of adverse reactions between the two groups.ConclusionTreatment with Danlou tablets and the modified combination therapy based on Western medicine treatment could improve angina pectoris symptoms of patients with SAP and IPBS syndrome and its concurrent syndromes, and improve patients’ quality of life. Furthermore, the treatment is safe, has a long-term prognosis, and is worth further promotion and application in clinical practice.Clinical Trial Registrationhttps://www.chictr.org.cn/showprojEN.html?proj=235570, ChiCTR registry, ChiCTR1900023708.

A unique approach for investigating skin lesions and their relationship with TCM syndrome differentiation in alopecia areata

Background: Alopecia areata is also known as ‘oil wind’ in Chinese medicine. Alopecia areata is a debilitating autoimmune skindisease characterized by patches of non-scarring hair loss and inflammation that damages the scalp and body hair in a variable,often relapsing or permanent fashion. It is not quite obvious how the various Traditional Chinese Medicine (TCM) syndromes differentiate between the skin lesions under dermatoscopy caused by alopecia areata. Objective: This study aimed to provide a rational basis for TCM syndrome differentiation of alopecia areata and investigate the role of skin lesions in various TCM syndromes of alopecia areata under dermatoscopy. Methods: The dermatologist used a dermatoscope to take four images of the patient's skin lesion area and the skin lesion junction. Two of the images were captured with polarized light, while the other two were taken with non-polarized light. Patients with alopecia areata who had TCM syndrome differentiation were identified and examined using dermatoscopy. The occurrence of the yellow dot, white dot, exclamation mark hair and vascular sign, was determined and then statistically analyzed. Results: The positive rates of vascular signs relate to alopecia areata, exclamation mark hair relates to Qi-blood deficiency and white dot corresponded to liver and kidney deficiency. All the positive rates were statistically significant (P < 0.05). Compared to vascular sign, white dot sign, and Qi-blood deficiency syndrome groups, the positive rate of yellow dot syndrome was not significant (P>0.05) Conclusion: The findings suggest that particular skin lesions contribute to differentiating different TCM syndromes associated with alopecia areata. Skin lesions examined under dermatoscopy can assist in diagnosing the TCM syndromes associated with alopecia areata. Keywords: Dermatoscopic signs; Alopecia areata; TCM syndromes; Qi and blood deficiency; Liver and kidney deficiency.

Association of miR-499 rs3746444, miR-149 rs2292832 polymorphisms and their expression levels with helicobacter pylori-related gastric diseases and Traditional Chinese Medicine syndromes.

To provide an objective experimental basis for the gastric mucosa pathological evolution and the transformation of different Traditional Chinese Medicine (TCM) syndromes in helicobacter pylori (H. pylori)-related gastric diseases (HPGD) patients, based on the combination of TCM syndrome differentiation, molecular biology and histopathology. A total of 203 participants were enrolled in this study. The expressions of miR-499/miR-149 and H. pylori infection in the gastric tissues from all participants were detected. The genotyping for miR-499 rs3746444 and miR-149 rs2292832 was performed. In H. pylori positive subjects, the proportion of precancerous gastric lesions (PGL) in liver-stomach disharmony syndrome (LSDS) group was higher than in spleen Qi deficiency syndrome (SQDS) group (P <0.001); The proportion of gastric cancer (GC) in SQDS group was higher than in spleen-stomach damp-heat syndrome (SSDHS) group and LSDS group (all P <0.001). We also found C allele of miR-149 rs2292832 was linked to lower risk of gastric atrophy [miR-149 rs2292832 C vs T: adjusted odds ratio = 0.207; 95% confidence interval (0.043-0.989); P = 0.048]. Compared with healthy control (HC) group, the expression of miR-499 was significantly increased in GC group, while the expression of miR-149 was significantly decreased in chronic inflammation group, PGL group and GC group (all P < 0.05). Test for trend showed that GC risk was on a rising trend with the increasing expression of miR-499 and decreasing expression of miR-149 (both P for trend < 0.05). The C allele of miR-149 rs2292832 may be a protective factor for gastric mucosal atrophy. H. pylori may participate in the evolution of benign to malignant gastric mucosa lesions by inducing the overexpression of miR-499 and down regulation of miR-149. In addition, patients with H. pylori infection combined SQDS or LSDS may have higher risk of gastric mucosal malignant lesions.

Discussion on the relationship between the distribution characteristics of TCM syndrome types and related objective indicators in hepatolenticular degeneration.

Hepatolenticular degeneration is a rare treatable autosomal recessive inherited copper metabolism disorder with a diverse clinical phenotype and an exceptionally complex pathogenesis. Early definitive phenotypic diagnosis and targeted treatment are major challenges worldwide. In this study, we strictly followed the "National Standards of the People's Republic of China - Terminology of Traditional Chinese Medicine Clinical Diagnosis and Treatment (Syndrome Part)," "Chinese Medicine Nomenclature," and the clinical investigation-determined traditional Chinese medicine syndrome differentiation standards at Anhui University of Chinese Medicine to select 6 of the most common traditional Chinese medicine syndrome differentiations. This study retrospectively analyzed 107 patients admitted between 2019 and 2023 with Wilson's disease based on real-world data. After testing for normal distribution and homogeneity of variance, corresponding analysis of variance was selected, followed by post hoc multiple comparisons. Of the selected 25 objective influencing factors, 22 exhibited normal distribution, while red blood cells, hemoglobin, and type IV collagen did not pass the homogeneity of variance test. After analysis of variance, the factors ceruloplasmin (CP) and copper oxidase (SCO) showed significant differences among patients with different traditional Chinese medicine syndromes (P < .05), with partial η2 for CP being 0.13 > 0.06 and for SCO being 0.143 > 0.14. Post hoc multiple comparison results indicated significant differences in CP and SCO among patients with certain traditional Chinese medicine syndromes (P < .05). There were significant differences in the factors CP and SCO among patients with different traditional Chinese medicine syndromes. Significant differences were observed in the copper blue protein factor between damp-heat syndrome and liver and kidney deficiency syndrome, liver and kidney deficiency syndrome and liver and kidney yin deficiency syndrome, liver and kidney deficiency syndrome and phlegm heat and wind syndrome, as well as liver and kidney deficiency syndrome and syndrome of phlegm and blood stasis (P < .05). Significant differences were also found in the SCO factor between damp-heat syndrome and liver and kidney deficiency syndrome, liver and kidney deficiency syndrome and liver and kidney yin deficiency syndrome, liver and kidney deficiency syndrome and phlegm heat and wind syndrome, and liver and kidney deficiency syndrome and syndrome of phlegm and blood stasis (P < .05).

Objective Analysis of Traditional Chinese Medicine Syndrome Differentiation of Patients With Diabetes and Prediabetes: Protocol for a Nonrandomized, Exploratory, Observational Case-Control Study Using Digitalized Traditional Chinese Medicine Diagnostic Tools.

Diabetes and prediabetes are diagnosed differentially by Western and Chinese medicine. While Western medicine uses objective laboratory analysis of biochemical parameters to define the severity of diabetes and prediabetes, Chinese medicine uses a comprehensive approach that integrates observation, inquiry, pulse palpation, and tongue diagnosis. The medical information collected is then categorized into different syndromes. However, traditional methods of pulse and tongue diagnoses used to determine syndrome differentiation are highly subjective and skill dependent. This study aims to identify the gap in conventional traditional Chinese medicine (TCM) diagnostic techniques for syndrome differentiation analysis using contemporary diagnostic devices. We devised a protocol for a nonrandomized, exploratory, observational case-control study with equal allocations in 5 arms to investigate the syndrome differentiation of diabetes and prediabetes. We hypothesize that the TCM syndrome differentiation of diabetes and prediabetes in the tropical climate may differ from that defined based on the Chinese demographic. We also speculate that the high-frequency spectral energy may reflect a difference in pulse wave intensity and density between the healthy and diabetes groups. A total of 250 eligible participants will be equally assigned to 1 of 5 arms (healthy or subhealthy, prediabetes, diabetes, prediabetes with hypertension and dyslipidemia, and diabetes with hypertension and dyslipidemia). Participants aged 21-75 years, of any sex or race, and have been diagnosed with diabetes (fasting plasma glucose [FPG] of 7 mmol/L, or 2-hour plasma glucose [2hPG] of 11.1 mmol/L) or prediabetes (impaired FPG of 6.1-6.9 mmol/L, or impaired glucose tolerance with an 2hPG of 7.8-11 mmol/L) will be included. The Health Evaluation Questionnaire, Physical Activity Questionnaire, sugar intake assessment, Constitution in Chinese Medicine Questionnaire, radial pulse diagnosis, and tongue diagnosis will be performed in a single visit. ANOVA for continuous data and chi-square tests of independence will be used for categorical data assessments, with a level of P<.05 considered significant. The recruitment is in progress. We anticipate that the study will conclude in June 2025. As of July 15, 2024, we have enrolled 140 individuals. To the best of our knowledge, this is the first study to use contemporary TCM diagnostic instruments to map expert and empirical knowledge of TCM to its scientific equivalents for the purpose of evaluating the syndrome differentiation of diabetes. We designed this protocol with the exploratory goal to examine objectively the syndrome differentiation of patients with diabetes and those with prediabetes using TCM diagnostic technologies. The data collected and evaluated under standardized conditions using these contemporary diagnostic devices will exhibit a higher degree of stability, hence yielding dependable and unbiased results for syndrome differentiation. Thus, our findings may potentially increase the accuracy of identification, diagnosis, treatment, and prevention of diabetes and prediabetes through a system of targeted treatment. ClinicalTrials.gov NCT05563090; https://clinicaltrials.gov/ct2/show/NCT05563090. DERR1-10.2196/56024.

Research Progress of TCM Treatment of Postoperative Constipation in Anorectal Diseases

Postoperative constipation for anorectal diseases is mainly manifested as dry stool due to pain and fear of defecation, slow bowel movement or improper diet, difficulty in defecation or even several days without defecation after anorectal diseases. It is a common disease after anorectal diseases, which not only affects postoperative wound healing, but also often causes psychological and mental diseases and acute cardiovasoular and cerebrovascular diseases. In severe cases, the postoperative recovery of patients is greatly affected. At present, through the treatment of Traditional Chinese Medicine (TCM) syndrome differentiation,TCM external treatment and other methods, has achieved good ourative effect. In this paper, the recent progress in the treatment of constipation after anorectal diseases by traditional Chinese medicine was summarized.

AI: Bridging Ancient Wisdom and Modern Innovation in Traditional Chinese Medicine.

The pursuit of groundbreaking health care innovations has led to the convergence of artificial intelligence (AI) and traditional Chinese medicine (TCM), thus marking a new frontier that demonstrates the promise of combining the advantages of ancient healing practices with cutting-edge advancements in modern technology. TCM, which is a holistic medical system with >2000 years of empirical support, uses unique diagnostic methods such as inspection, auscultation and olfaction, inquiry, and palpation. AI is the simulation of human intelligence processes by machines, especially via computer systems. TCM is experience oriented, holistic, and subjective, and its combination with AI has beneficial effects, which presumably arises from the perspectives of diagnostic accuracy, treatment efficacy, and prognostic veracity. The role of AI in TCM is highlighted by its use in diagnostics, with machine learning enhancing the precision of treatment through complex pattern recognition. This is exemplified by the greater accuracy of TCM syndrome differentiation via tongue images that are analyzed by AI. However, integrating AI into TCM also presents multifaceted challenges, such as data quality and ethical issues; thus, a unified strategy, such as the use of standardized data sets, is required to improve AI understanding and application of TCM principles. The evolution of TCM through the integration of AI is a key factor for elucidating new horizons in health care. As research continues to evolve, it is imperative that technologists and TCM practitioners collaborate to drive innovative solutions that push the boundaries of medical science and honor the profound legacy of TCM. We can chart a future course wherein AI-augmented TCM practices contribute to more systematic, effective, and accessible health care systems for all individuals.

HHO optimized support vector machine classifier for traditional Chinese medicine syndrome differentiation of diabetic retinopathy.

To develop a classifier for traditional Chinese medicine (TCM) syndrome differentiation of diabetic retinopathy (DR), using optimized machine learning algorithms, which can provide the basis for TCM objective and intelligent syndrome differentiation. Collated data on real-world DR cases were collected. A variety of machine learning methods were used to construct TCM syndrome classification model, and the best performance was selected as the basic model. Genetic Algorithm (GA) was used for feature selection to obtain the optimal feature combination. Harris Hawk Optimization (HHO) was used for parameter optimization, and a classification model based on feature selection and parameter optimization was constructed. The performance of the model was compared with other optimization algorithms. The models were evaluated with accuracy, precision, recall, and F1 score as indicators. Data on 970 cases that met screening requirements were collected. Support Vector Machine (SVM) was the best basic classification model. The accuracy rate of the model was 82.05%, the precision rate was 82.34%, the recall rate was 81.81%, and the F1 value was 81.76%. After GA screening, the optimal feature combination contained 37 feature values, which was consistent with TCM clinical practice. The model based on optimal combination and SVM (GA_SVM) had an accuracy improvement of 1.92% compared to the basic classifier. SVM model based on HHO and GA optimization (HHO_GA_SVM) had the best performance and convergence speed compared with other optimization algorithms. Compared with the basic classification model, the accuracy was improved by 3.51%. HHO and GA optimization can improve the model performance of SVM in TCM syndrome differentiation of DR. It provides a new method and research idea for TCM intelligent assisted syndrome differentiation.

An interpretability model for syndrome differentiation of HBV-ACLF in traditional Chinese medicine using small-sample imbalanced data

ObjectiveClinical medical record data associated with hepatitis B-related acute-on-chronic liver failure (HBV-ACLF) generally have small sample sizes and a class imbalance. However, most machine learning models are designed based on balanced data and lack interpretability. This study aimed to propose a traditional Chinese medicine (TCM) diagnostic model for HBV-ACLF based on the TCM syndrome differentiation and treatment theory, which is clinically interpretable and highly accurate. MethodsWe collected medical records from 261 patients diagnosed with HBV-ACLF, including three syndromes: Yang jaundice (214 cases), Yang-Yin jaundice (41 cases), and Yin jaundice (6 cases). To avoid overfitting of the machine learning model, we excluded the cases of Yin jaundice. After data standardization and cleaning, we obtained 255 relevant medical records of Yang jaundice and Yang-Yin jaundice. To address the class imbalance issue, we employed the oversampling method and five machine learning methods, including logistic regression (LR), support vector machine (SVM), decision tree (DT), random forest (RF), and extreme gradient boosting (XGBoost) to construct the syndrome diagnosis models. This study used precision, F1 score, the area under the receiver operating characteristic (ROC) curve (AUC), and accuracy as model evaluation metrics. The model with the best classification performance was selected to extract the diagnostic rule, and its clinical significance was thoroughly analyzed. Furthermore, we proposed a novel multiple-round stable rule extraction (MRSRE) method to obtain a stable rule set of features that can exhibit the model’s clinical interpretability. ResultsThe precision of the five machine learning models built using oversampled balanced data exceeded 0.90. Among these models, the accuracy of RF classification of syndrome types was 0.92, and the mean F1 scores of the two categories of Yang jaundice and Yang-Yin jaundice were 0.93 and 0.94, respectively. Additionally, the AUC was 0.98. The extraction rules of the RF syndrome differentiation model based on the MRSRE method revealed that the common features of Yang jaundice and Yang-Yin jaundice were wiry pulse, yellowing of the urine, skin, and eyes, normal tongue body, healthy sublingual vessel, nausea, oil loathing, and poor appetite. The main features of Yang jaundice were a red tongue body and thickened sublingual vessels, whereas those of Yang-Yin jaundice were a dark tongue body, pale white tongue body, white tongue coating, lack of strength, slippery pulse, light red tongue body, slimy tongue coating, and abdominal distension. This is aligned with the classifications made by TCM experts based on TCM syndrome differentiation and treatment theory. ConclusionOur model can be utilized for differentiating HBV-ACLF syndromes, which has the potential to be applied to generate other clinically interpretable models with high accuracy on clinical data characterized by small sample sizes and a class imbalance.

Research progress of Chinese herbal medicines and classic prescriptions in the treatment of COPD based on the TCM theory and medicinal characteristics

Abstract Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with a complex pathogenesis, which causes the lack of precise and personalized prevention, control, and treatment approaches in clinical practice. Traditional Chinese medicine (TCM) with multiple components acting on multiple targets plays a role in the prevention and treatment of COPD. After evaluating the treatment of cough, dyspnea, and lung distension based on syndrome differentiation in TCM, we summarized the commonly used TCM preparations for treating COPD. These preparations are mainly composed of medicines for clearing interior heat and releasing exterior, tonifying, activating blood and resolving stasis, resolving phlegm, relieving cough and breathlessness, and regulating Qi movement. Because all of them contain a variety of active ingredients such as flavonoids, terpenoids, and phenols, we analyzed the mechanisms of the classic prescriptions alone or in combination with other medicines or therapeutic methods. These mechanisms involve counteracting inflammation, oxidative stress, and fibrosis, inhibiting apoptosis, alleviating airway remodeling, and enhancing immunity. Meantime, we summarized the existing problems in the treatment of COPD by TCM. This review provides a scientific basis for the research and treatment of COPD in the future.

Study on the difference and regularity of tongue images in 309 patients with different pathological stages of non-small cell lung cancer.

Tongue diagnosis is a crucial traditional Chinese medicine (TCM) inspection method for TCM syndrome differentiation and treatment. The primary research focus was on tongue image characteristic parameters of patients with non-small cell lung cancer (NSCLC). Analysis of the tongue image parameters of various pathological stages of NSCLC provides technical support for establishing an integrated Chinese and Western auxiliary diagnosis and efficacy evaluation medicine system for lung cancer that integrates tongue image features. Tongue image characteristics of 309 patients with NSCLC and 206 controls were collected and analyzed clinically. The T-test or rank sum test and logistic regression analysis were applied to analyze the characteristics of tongue image indicators of different pathological stages of NSCLC. There were differences in tongue image characteristics in the NSCLC group compared to the control group. The tongue quality and brightness of the tongue coating in the NSCLC group increased, the red component was reduced, the tongue coating thickened, and the yellow component increased compared to the healthy control group. A comparison of tongue image indexes of NSCLC in different pathological stages showed that stage IV had lower TB-b and higher TB-a than stage I. In addition, stage IV had lower TB-b than stage II + III, showing an increase in the blue and red components of the tongue in stage IV and the appearance of cyanotic tongue features. The tongue image characteristics of NSCLC patients differed from those of the control group. Tongue imaging indicators can reflect the characteristics of tongue images of patients with NSCLC. The tongue image characteristics of patients with stage IV lung cancer are bluish and purple compared with those with stage I, II, and III. It is suggested that the tongue's image characteristics can be used as a reference for the pathological classification of NSCLC and judgment of the disease process.

PresRecST: a novel herbal prescription recommendation algorithm for real-world patients with integration of syndrome differentiation and treatment planning.

Herbal prescription recommendation (HPR) is a hot topic and challenging issue in field of clinical decision support of traditional Chinese medicine (TCM). However, almost all previous HPR methods have not adhered to the clinical principles of syndrome differentiation and treatment planning of TCM, which has resulted in suboptimal performance and difficulties in application to real-world clinical scenarios. We emphasize the synergy among diagnosis and treatment procedure in real-world TCM clinical settings to propose the PresRecST model, which effectively combines the key components of symptom collection, syndrome differentiation, treatment method determination, and herb recommendation. This model integrates a self-curated TCM knowledge graph to learn the high-quality representations of TCM biomedical entities and performs 3 stages of clinical predictions to meet the principle of systematic sequential procedure of TCM decision making. To address the limitations of previous datasets, we constructed the TCM-Lung dataset, which is suitable for the simultaneous training of the syndrome differentiation, treatment method determination, and herb recommendation. Overall experimental results on 2 datasets demonstrate that the proposed PresRecST outperforms the state-of-the-art algorithm by significant improvements (eg, improvements of P@5 by 4.70%, P@10 by 5.37%, P@20 by 3.08% compared with the best baseline). The workflow of PresRecST effectively integrates the embedding vectors of the knowledge graph for progressive recommendation tasks, and it closely aligns with the actual diagnostic and treatment procedures followed by TCM doctors. A series of ablation experiments and case study show the availability and interpretability of PresRecST, indicating the proposed PresRecST can be beneficial for assisting the diagnosis and treatment in real-world TCM clinical settings. Our technology can be applied in a progressive recommendation scenario, providing recommendations for related items in a progressive manner, which can assist in providing more reliable diagnoses and herbal therapies for TCM clinical task.

Analysis of clinical evidence on traditional Chinese medicine for the treatment of diabetic nephropathy: a comprehensive review with evidence mapping.

This study aims to map evidence from Randomized Controlled Trials (RCTs) and systematic reviews/Meta-analyses concerning the treatment of Diabetic Nephropathy (DN) with Traditional Chinese Medicine (TCM), understand the distribution of evidence in this field, and summarize the efficacy and existing problems of TCM in treating DN. The intention is to provide evidence-based data for TCM in preventing and treating DN and to offer a reference for defining future research directions. Comprehensive searches of major databases were performed, spanning from January 2016 to May 2023, to include clinical RCTs and systematic reviews/Meta-analyses of TCM in treating DN. The analysis encompasses the publishing trend of clinical studies, the staging of research subjects, TCM syndrome differentiation, study scale, intervention plans, and outcome indicators. Methodological quality of systematic reviews was evaluated using the AMSTAR (Assessment of Multiple Systematic Reviews) checklist, and evidence distribution characteristics were analyzed using a combination of text and charts. A total of 1926 RCTs and 110 systematic reviews/Meta-analyses were included. The majority of studies focused on stage III DN, with Qi-Yin deficiency being the predominant syndrome type, and sample sizes most commonly ranging from 60 to 100. The TCM intervention durations were primarily between 12-24 weeks. Therapeutic measures mainly consisted of Chinese herbal decoctions and patented Chinese medicines, with a substantial focus on clinical efficacy rate, TCM symptomatology, and renal function indicators, while attention to quality of life, dosage of Western medicine, and disease progression was inadequate. Systematic reviews mostly scored between 5 and 8 on the AMSTAR scale, and evidence from 94 studies indicated potential positive effects. DN represents a significant health challenge, particularly for the elderly, with TCM showing promise in symptom alleviation and renal protection. Yet, the field is marred by research inconsistencies and methodological shortcomings. Future investigations should prioritize the development of standardized outcome sets tailored to DN, carefully select evaluation indicators that reflect TCM's unique intervention strategies, and aim to improve the robustness of clinical evidence. Emphasizing TCM's foundational theories while incorporating advanced scientific technologies will be essential for innovating research methodologies and uncovering the mechanisms underlying TCM's efficacy in DN management.

Out-of-set association analysis of lung cancer drugs and symptoms based on clinical case data mining.

There are 1.8 million lung cancer deaths worldwide, accounting for 18% of global cancer deaths, including 710,000 in China, accounting for 23.8% of all cancer deaths in China. To explore the out-of-set association rules of lung cancer symptoms and drugs through text mining of traditional Chinese medicine (TCM) treatment of lung cancer, and form medical case analysis to analyze the experience of TCM syndrome differentiation in its treatment. The medical records of all patients diagnosed with lung cancer in Nanjing Chest Hospital from January to December 2018 were collected, and the out-of-set association analysis was performed using the MedCase v5.2 TCM clinical scientific research auxiliary platform based on the frequent pattern growth enhanced association analysis algorithm. In terms of TCM treatment of lung cancer, the clinical symptoms with high correlation included cough, expectoration, chest distress, and white phlegm; and the drugs with high correlation included Pinellia ternata, licorice root, white Atractylodes rhizome, and Radix Ophiopogonis; with the prescriptions based on Erchen and Maimendong decoctions. This analytical study of the medical cases of TCM treatment for lung cancer was performed using data mining techniques, and the out-of-set association rules between clinical symptoms and drugs were analyzed, including the understanding of lung cancer in TCM. Moreover, the essence of experience in drug use was gathered, providing significant scientific guidance for the clinical treatment of lung cancer.

TCMSSD: A comprehensive database focused on syndrome standardization

BackgroudQuantitative and standardized research on syndrome differentiation has always been at the forefront of modernizing Traditional Chinese Medicine (TCM) theory. However, the majority of existing databases primarily concentrate on the network pharmacology of herbal prescriptions, and there are limited databases specifically dedicated to TCM syndrome differentiation. PurposeIn response to this gap, we have developed the Traditional Chinese Medical Syndrome Standardization Database (TCMSSD, http://tcmssd.ratcm.cn). MethodsTCMSSD is a comprehensive database that gathers data from various sources, including TCM literature such as TCM Syndrome Studies (Zhong Yi Zheng Hou Xue) and TCM Internal Medicine (Zhong Yi Nei Ke Xue) and various public databases such as TCMID and ETCM. In our study, we employ a deep learning approach to construct the knowledge graph and utilize the BM25 algorithm for syndrome prediction. ResultsThe TCMSSD integrates the essence of TCM with the modern medical system, providing a comprehensive collection of information related to TCM. It includes 624 syndromes, 133,518 prescriptions, 8,073 diseases (including 1,843 TCM-specific diseases), 8,259 Chinese herbal medicines, 43,413 ingredients, 17,602 targets, and 8,182 drugs. By analyzing input data and comparing it with the patterns and characteristics recorded in the database, the syndrome prediction tool generates predictions based on established correlations and patterns. ConclusionThe TCMSSD fills the gap in existing databases by providing a comprehensive resource for quantitative and standardized research on TCM syndrome differentiation and laid the foundation for research on the biological basis of syndromes.

Construction and Application of a Traditional Chinese Medicine Syndrome Differentiation Model for Dysmenorrhea Based on Machine Learning.

Dysmenorrhea is one of the most common ailments affecting young and middle-aged women, significantly impacting their quality of life. Traditional Chinese Medicine (TCM) offers unique advantages in treating dysmenorrhea. However, an accurate diagnosis is essential to ensure correct treatment. This research integrates the age-old wisdom of TCM with modern Machine Learning (ML) techniques to enhance the precision and efficiency of dysmenorrhea syndrome differentiation, a pivotal process in TCM diagnostics and treatment planning. A total of 853 effective cases of dysmenorrhea were retrieved from the CNKI database, including patients' syndrome types, symptoms, and features, to establish the TCM information database of dysmenorrhea. Subsequently, 42 critical features were isolated from a potential set of 86 using a selection procedure augmented by Python's Scikit-Learn Library. Various machine learning models were employed, including Logistic Regression, Random Forest Classifier, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Artificial Neural Networks (ANN), each chosen for their potential to unearth complex patterns within the data. Based on accuracy, precision, recall, and F1-score metrics, SVM emerged as the most effective model, showcasing an impressive precision of 98.29% and an accuracy of 98.24%. This model's analytical prowess not only highlighted the critical features pivotal to the syndrome differentiation process but also stands to significantly aid clinicians in formulating personalized treatment strategies by pinpointing nuanced symptoms with high precision. The study paves the way for a synergistic approach in TCM diagnostics, merging ancient wisdom with computational acuity, potentially innovating the diagnosis and treatment mode of TCM. Despite the promising outcomes, further research is needed to validate these models in real-world settings and extend this approach to other diseases addressed by TCM.

Comprehensive effects of traditional Chinese medicine treatment on heart failure and changes in B-type natriuretic peptide levels: A meta-analysis.

Heart failure (HF), a common cardiovascular condition, is characterized by significant morbidity and mortality. While traditional Chinese medicine (TCM) is often used as a complementary approach in HF management, systematic evaluations of its impact on clinical outcomes, TCM syndrome scores, and B-type natriuretic peptide (BNP) levels are lacking. This study fills this gap through a comprehensive analysis of randomized controlled trials (RCTs) focusing on TCM for HF treatment. It encompasses an assessment of methodological quality, a meta-analysis, and an evaluation of evidence quality based on established standards. The results offer crucial insights into the potential advantages and constraints of TCM in HF management. To systematically analyze the effects of TCM on the clinical comprehensive outcomes, TCM syndrome scores, and BNP levels in patients with HF and evaluated the quality of evidence for these trials. RCTs on TCM for HF treatment published since the establishment of the database were searched in four Chinese and English databases, including China National Knowledge Infrastructure, Wanfang, VIP Information Chinese Science and Technology Journal, and PubMed. Methodological quality was assessed for the included studies with the Cochrane risk-of-bias assessment tool, and the meta-analysis and publication bias assessment was performed with the RevMan5.3 software. Finally, the quality of evidence was rated according to the GRADE criteria. A total of 1098 RCTs were initially retrieved. After screening, 16 RCTs were finally included in our study, which were published between 2020 and 2023. These RCTs involved 1660 HF patients, including 832 in the TCM group [TCM combined with conventional Western medicine (CMW) treatment] and 828 in the CWM group (CWM treatment). The course of treatments varied from 1 wk to 3 months. TCM syndrome differentiation was analyzed in 11 of the included RCTs. In all included RCTs, outcome indicators included comprehensive clinical outcomes, TCM syndrome scores, and BNP levels. The meta-analysis results showed significant differences between the TCM and CWM groups in terms of comprehensive clinical outcomes [risk ratio = -0.54; 95% confidence interval (CI) = -0.61, -0.47; P < 0.00001], TCM syndrome scores [weighted mean difference (WMD) = -142.07; 95%CI = -147.56, -136.57; P < 0.00001], and BNP levels (WMD = -142.07; 95%CI = -147.56, -136.57; P < 0.00001). According to the GRADE criteria, RCTs where "TCM improves clinical comprehensive outcomes" were rated as low-quality evidence, and RCTs where "TCM reduces TCM syndrome scores" or "TCM decreases BNP levels" were rated as medium-quality evidence. TCM combined with CWM treatment effectively improves comprehensive clinical outcomes and diminishes TCM syndrome scores and BNP levels in HF patients. Given the low and medium quality of the included RCTs, the application of these results should be cautious.

Clinical Effect of Modified Shengyang Yiwei Decoction in the Treatment of Diarrhea-Predominant Irritable Bowel Syndrome due to Spleen and Stomach Weakness

Objective: To explore the therapeutic effect of Shengyang Yiwei Decoction in patients with diarrhea-predominant irritable bowel syndrome (IBS) due to spleen and stomach weakness. Methods: 40 patients with diarrhea-predominant IBS who were treated from April 2018 to April 2020 were taken as samples. TCM (traditional Chinese medicine) syndrome differentiation found that they were all due to spleen and stomach weakness. They were randomly divided into two groups. Group A was treated with modified prescriptions of Shengyang Yiwei Decoction, while Group B was treated with Western medicine. The therapeutic effects in the two groups were compared. Results: The treatment efficacy in Group A was higher than that in Group B (P &lt; 0.05); the symptom scores of Group A such as loose stools, chills, physical weakness, poor appetite, and abdominal distension after meals were all lower than those in Group B (P&lt; 0.05); the SF-36 (36-Item Short Form Health Survey) scores of patients with diarrhea-predominant IBS in Group A were higher than those in Group B (P &lt; 0.05); the treatment satisfaction of Group A was higher than that of Group B (P&lt; 0.05). Conclusion: Treatment of diarrhea-predominant IBS patients with spleen and stomach weakness by Shengyang Yiwei Decoction can promote the disappearance of gastrointestinal discomfort symptoms, improve the quality of life, and enhance treatment efficacy. Hence, it is an efficient and feasible treatment for diarrhea-predominant IBS due to spleen and stomach weakness.

Differential clinical characteristics across traditional Chinese medicine (TCM) Syndromes in patients with sickle cell disease.

Pain is a common, debilitating, and poorly understood complication of sickle cell disease (SCD). The need for clinical pain management of SCD is largely unmet and relies on opioids as the main therapeutic option, which leads to a decreased quality of life (QoL). According to the literature, acupuncture has shown certain therapeutic effects for pain management in SCD. However, these clinical studies lack the guidance of Traditional Chinese Medicine (TCM) Syndrome Differentiation principles for treatment. To characterize differences in clinical presentation amongst TCM diagnosed Syndromes in SCD patients. Fifty-two patients with SCD and 28 age- and sex-matched healthy controls (HCs) were enrolled in an ongoing trial of acupuncture. Each participant completed a series of questionnaires on pain, physical function, fatigue, sleep, anxiety, depression and QoL and underwent cold- and pressure-based quantitative sensory testing at baseline. Data on prescription opioid use over the 12 months prior to study enrollment was used to calculate mean daily morphine milligram equivalents (MME). Differences among the three TCM Syndromes were analyzed by one-way ANOVA followed by Tukey post hoc testing. Two-sample t-tests were used to compare SCD and HC groups. TCM diagnosis criteria classified SCD patients into one of three TCM Syndromes: (a) Equal; (b) Deficiency; and (c) Stagnation. The Stagnation group exhibited higher pain interference, physical dysfunction, nociplastic pain, fatigue, anxiety, depression, MME consumption and lower sleep quality and QoL compared to the Equal group. Few differences were observed between HCs and the Equal SCD group across outcomes. Deficiency and Stagnation groups were differentiated with observed- and patient-reported clinical manifestations. These findings suggest that TCM diagnosed Syndromes in SCD can be differentially characterized using validated objective and patient-reported outcomes. Because characteristics of pain and co-morbidities in each SCD patient are unique, targeting specific TCM "Syndromes" may facilitate treatment effectiveness with a Syndrome-based personalized treatment plan that conforms to TCM principles. These findings lay the foundation for the development of tailored acupuncture interventions based on TCM Syndromes for managing pain in SCD. Larger samples are required to further refine and validate TCM diagnostic criteria for SCD.

Network medicine analysis for dissecting the therapeutic mechanism of consensus TCM formulae in treating hepatocellular carcinoma with different TCM syndromes.

Hepatocellular carcinoma (HCC) is a major cause of cancer-related mortality worldwide. Traditional Chinese Medicine (TCM) is widely utilized as an adjunct therapy, improving patient survival and quality of life. TCM categorizes HCC into five distinct syndromes, each treated with specific herbal formulae. However, the molecular mechanisms underlying these treatments remain unclear. We employed a network medicine approach to explore the therapeutic mechanisms of TCM in HCC. By constructing a protein-protein interaction (PPI) network, we integrated genes associated with TCM syndromes and their corresponding herbal formulae. This allowed for a quantitative analysis of the topological and functional relationships between TCM syndromes, HCC, and the specific formulae used for treatment. Our findings revealed that genes related to the five TCM syndromes were closely associated with HCC-related genes within the PPI network. The gene sets corresponding to the five TCM formulae exhibited significant proximity to HCC and its related syndromes, suggesting the efficacy of TCM syndrome differentiation and treatment. Additionally, through a random walk algorithm applied to a heterogeneous network, we prioritized active herbal ingredients, with results confirmed by literature. The identification of these key compounds underscores the potential of network medicine to unravel the complex pharmacological actions of TCM. This study provides a molecular basis for TCM's therapeutic strategies in HCC and highlights specific herbal ingredients as potential leads for drug development and precision medicine.