BACKGROUND: Clinical studies have shown that diabetic peripheral neuropathy (DPN) has been on the rise, with most patients presenting with severe and progressive symptoms. Currently, most of the available prediction models for DPN are derived from general clinical information and laboratory indicators. Several Traditional Chinese medicine (TCM) indicators have been utilised to construct prediction models. In this study, we established a novel machine learning-based multi-featured Chinese-Western medicine-integrated prediction model for DPN using clinical features of TCM.
METHODS: The clinical data of 1581 patients with Type 2 diabetes mellitus (T2DM) treated at the Department of Endocrinology of the First Affiliated Hospital of Anhui University of Chinese Medicine were collected. The data (including general information, laboratory parameters and TCM features) of 1142 patients with T2DM were selected after data cleaning. After baseline description analysis of the variables, the data were divided into training and validation sets. Four prediction models were established and their performance was evaluated using validation sets. Meanwhile, the accuracy, precision, recall, F1 score and area under the curve (AUC) of ROC were calculated using ten-fold cross-validation to further assess the performance of the models. An explanatory analysis of the results of the DPN prediction model was carried out using the SHAP framework based on machine learning-based prediction models.
RESULTS: Of the 1142 patients with T2DM, 681 had a comorbidity of DPN, while 461 did not. There was a significant difference between the two groups in terms of age, cause of disease, systolic pressure, HbA1c, ALT, RBC, Cr, BUN, red blood cells in the urine, glucose in the urine, and protein in the urine (p < 0.05). T2DM patients with a comorbidity of DPN exhibited diverse TCM symptoms, including limb numbness, limb pain, hypodynamia, thirst with desire for drinks, dry mouth and throat, blurred vision, gloomy complexion, and unsmooth pulse, with statistically significant differences (p < 0.05). Our results showed that the proposed multi-featured Chinese-Western medicine-integrated prediction model was superior to conventional models without characteristic TCM indicators. The model showed the best performance (accuracy = 0.8109, precision = 0.8029, recall = 0.9060, F1 score = 0.8511, and AUC = 0.9002). SHAP analysis revealed that the dominant risk factors that caused DPN were TCM symptoms (limb numbness, thirst with desire for drinks, blurred vision), age, cause of disease, and glycosylated haemoglobin. These risk factors were exerted positive effects on the DPN prediction models.
CONCLUSIONS: A multi-feature, Chinese-Western medicine-integrated prediction model for DPN was established and validated. The model improves early-stage identification of high-risk groups for DPN in the diagnosis and treatment of T2DM, while also providing informative support for the intelligent management of chronic conditions such as diabetes.

OBJECTIVE: To investigate the metabolic mechanisms of Chinese and Western medicines on the metabolic network of striatal injury in a copper-loaded rat model of Wilson disease (WD) from a metabolomic perspective.
METHODS: We divided 60 rats into 4 groups of 15 rats each according to a random number table, namely the control group, the model group, the Bushen Huoxue Huazhuo Recipe group, and the penicillamine group, and subsequently replicated the WD copper-loaded rat model according to the literature method for a total of 12 weeks. From the 7th week onwards, each intervention group was given an equivalent dose of the corresponding drug, and the control and model groups were given an equal volume of saline gavage until the end of the model replication. We used 1H NMR metabolomics techniques combined with multivariate statistical methods to describe the changes in the striatal metabolic profile of nerve injury in Wilson\'s disease and to analyze the effect of different treatments on their biomarker interventions.
RESULTS: Nerve cell damage was evident in the WD copper-loaded rat model and could be reduced to varying degrees by different methods of intervention in the striatal nerve cells. The content of glycine, serine metabolism, and valine metabolism decreased in WD copper-loaded rat model; aspartate content increased after penicillamine intervention; glycolytic metabolism, valine metabolism, taurine metabolism, and tyrosine metabolism increased in the group of Bushen Huoxue Huazhuo Recipe.
CONCLUSIONS: Different intervention methods of Chinese and Western medicine affect aspartate, glycolysis, taurine, tyrosine, valine, and carbon metabolism in striatal tissues of WD copper-loaded rats, and can regulate the metabolism of small molecules, which in turn have certain repairing effects on nerve damage in WD copper-loaded rats.

OBJECTIVE: This study evaluated the efficacy of traditional Chinese and western medicine combined with chronic disease management on rehabilitation of chronic obstructive pulmonary disease (COPD) patients.
METHODS: A total of 199 COPD patients in Shanghai Construction Group (SCG) Hospital were recruited as research objects. The control group (CG) consisted of 100 patients treated with conventional western chronic disease management, and the research group (RG) consisted of 99 patients treated with chronic disease management with combined traditional Chinese and western medicine. The efficacy, pulmonary rehabilitation performance, compliance score, 6-minute walk test (6MWT), modified Medical Research Council dyspnoea scale (MMRC), COPD assessment test (CAT), pulmonary function (PaO2, PaCO2, FEV1, PEF), self-rating anxiety scale (SAS), self-rating depression scale (SDS) and patient satisfaction between the two groups were compared.
RESULTS: Pulmonary rehabilitation performance, 6MWT results, and patient satisfaction in the RG were significantly better than those in the CG. The total effective rate, compliance score, PaO2, FEV1 and PEF of the RG were significantly higher than those of the CG. After treatment, the COPD symptom score, CAT score, PaCO2, SAS score and SDS score in the RG were significantly lower than those in the CG.
CONCLUSIONS: Chronic disease management with combined traditional Chinese and western medicine has great application value and high efficacy in pulmonary rehabilitation.

Based on the clinical characteristics of chronic atrophic gastritis in traditional Chinese and Western medicine, the domestic and foreign relevant literature reports and animal models of chronic atrophic as well as the clinical diagnostic indicators of traditional Chinese and western medicine, chronic atrophic gastritis evaluation standard was summarized to evaluate and analyze the coincidence degree of clinical symptoms of the existing chronic atrophic gastritis animal models. The statistical results found that modeling methods with a higher coincidence degree with the existing chronic atrophic gastritis animal models are disease and syndrome combination mode-ling, surgical modeling, multifactor comprehensive modeling and MNNG modeling. Although the animal models were reproduced by such methods as etiology, pathogenesis and disease and syndrome combination similar to those of human beings, there is still a big gap with the natural disease state. Further in-depth studies and improvement shall be made in clinical practice in the hope to provide refe-rence for clinical practice and experimental studies of chronic atrophic gastritis.