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Objective: To assess efficacy of Chinese medicine (CM) on insomnia considering characteristics of treatment based on syndrome differentiation., Methods: A total of 116 participants aged 18 to 65 years with moderate and severe primary insomnia were randomized to the placebo (n=20) or the CM group (n=96) for a 4-week treatment and a 4-week follow-up. Three CM clinicians independently prescribed treatments for each patient based on syndromes differentiation. The primary outcome was change in total sleep time (TST) from baseline. Secondary endpoints included sleep onset latency (SOL), wake time after sleep onset (WASO), sleep efficiency, Pittsburgh Sleep Quality Index (PSQI) and CM symptoms., Results: The CM group had an average 0.6 h more (95% confidence interval (CI): 0.3-0.9, P<0.001) TST and 34.1% (10.3%-58.0%, P=0.005) more patients beyond 0.5 h TST increment than that of the placebo group. PSQI was changed -3.3 (-3.8 to -2.7) in the CM group, a -2.0 (-3.2 to -0.8, P<0.001) difference from the placebo group. The CM symptom score in the CM group decreased -2.0 (-3.3 to -0.7, P=0.003) more than the placebo group. SOL and WASO changes were not significantly different between groups. The analysis of prescriptions by these clinicians revealed blood deficiency and Liver stagnation as the most common syndromes. Prescriptions for these clinicians displayed relative stability, while the herbs varied. All adverse events were mild and were not related to study treatment., Conclusion: CM treatment based on syndrome differentiation can increase TST and improve sleep quality of primary insomnia. It is effective and safe for primary insomnia. In future studies, the long-term efficacy validation and the exploratory of eutherapeutic clinicians' fixed herb formulas should be addressed (Registration No. NCT01613183)., (© 2024. The Chinese Journal of Integrated Traditional and Western Medicine Press and Springer-Verlag GmbH Germany, part of Springer Nature.)

Objective: To derive the Chinese medicine (CM) syndrome classification and subgroup syndrome characteristics of ischemic stroke patients., Methods: By extracting the CM clinical electronic medical records (EMRs) of 7,170 hospitalized patients with ischemic stroke from 2016 to 2018 at Weifang Hospital of Traditional Chinese Medicine, Shandong Province, China, a patient similarity network (PSN) was constructed based on the symptomatic phenotype of the patients. Thereafter the efficient community detection method BGLL was used to identify subgroups of patients. Finally, subgroups with a large number of cases were selected to analyze the specific manifestations of clinical symptoms and CM syndromes in each subgroup., Results: Seven main subgroups of patients with specific symptom characteristics were identified, including M3, M2, M1, M5, M0, M29 and M4. M3 and M0 subgroups had prominent posterior circulatory symptoms, while M3 was associated with autonomic disorders, and M4 manifested as anxiety; M2 and M4 had motor and motor coordination disorders; M1 had sensory disorders; M5 had more obvious lung infections; M29 had a disorder of consciousness. The specificity of CM syndromes of each subgroup was as follows. M3, M2, M1, M0, M29 and M4 all had the same syndrome as wind phlegm pattern; M3 and M0 both showed hyperactivity of Gan (Liver) yang pattern; M2 and M29 had similar syndromes, which corresponded to intertwined phlegm and blood stasis pattern and phlegm-stasis obstructing meridians pattern, respectively. The manifestations of CM syndromes often appeared in a combination of 2 or more syndrome elements. The most common combination of these 7 subgroups was wind-phlegm. The 7 subgroups of CM syndrome elements were specifically manifested as pathogenic wind, pathogenic phlegm, and deficiency pathogens., Conclusions: There were 7 main symptom similarity-based subgroups in ischemic stroke patients, and their specific characteristics were obvious. The main syndromes were wind phlegm pattern and hyperactivity of Gan yang pattern., (© 2022. The Chinese Journal of Integrated Traditional and Western Medicine Press and Springer-Verlag GmbH Germany, part of Springer Nature.)

Chinese medicine (CM) is a discipline with its own distinct methodologies and philosophical principles. The main method of treatment in CM is to use herbal prescriptions. Typically, a number of herbs are combined to form a formula and different formulae are prescribed for different patients. Regularities in the mixture of herbs in the prescriptions are important for both clinical treatment and novel patent medicine development. In this study, we analyze CM formula data using latent tree (LT) models. Interesting regularities are discovered. Those regularities are of interest to students of CM as well as pharmaceutical companies that manufacture medicine using Chinese herbs.

Objective: To explore the most effective herbal combinations commonly used by highly experienced Chinese medicine (CM) physicians for the treatment of insomnia., Methods: We collected and analyzed data related to insomnia treatment from the clinics of 7 highly experienced CM physicians in Beijing. The sample included 162 patients and 460 consultations in total. Patient outcomes, such as sleep quality and sleep time per day, were manually collected from the medical records by trained CM clinicians. Three data mining methods, support vector machine (SVM), logistic regression and decision tree, and multifactor dimensionality reduction (MDR), were used to determine and confirm the herbal combinations that resulted in positive outcomes in patients suffering from insomnia., Results: Results show that MDR is the most efficient method to predict the effective herbal combinations. Using the MDR model, we identified several combinations of herbs with 100% positive outcomes, such as stir-fried spine date seed, Szechwan lovage rhizome, and prepared thinleaf milkwort root; white peony root, golden thread, and stir-fried spine date seed; and Asiatic cornelian cherry fruit with fresh rehmannia., Conclusions: Results indicate that herbal combinations are effective treatments for patients with insomnia compared with individual herbs. It is also shown that MDR is a potent data mining method to identify the herbal combination with high rates of positive outcome.

Objective: To find an appropriate feature representation in the biclustering of symptom-herb relationship in Chinese medicine (CM)., Methods: Four different representation schemes were tested in identifying the complex relationship between symptoms and herbs using a biclustering algorithm on an insomnia data set. These representation schemes were effective count, binary value, relative success ratio, or modified relative success ratio. The comparison of the schemes was made on the number and size of biclusters with respect to different threshold values., Results and Conclusions: The modified relative success ratio scheme was the most appropriate feature representation among the four tested. Some of the biclusters selected from this representation scheme were known to follow the therapeutic principles of CM, while others may offer clues for further clinical investigations.