ObjectiveTo systematically evaluate the methodological quality and measurement properties of traditional Chinese medicine （TCM） syndrome efficacy evaluation scales， and to provide evidence-based references for selecting high-quality assessment tools in TCM clinical practice. MethodsChina National Knowledge Infrastructure （CNKI）， Wanfang Data， VIP Database， Chinese Biomedical Literature Database （CBM）， PubMed， the Cochrane Library， Embase， and Web of Science were searched from inception to April 2， 2025， for studies evaluating the measurement properties of TCM syndrome efficacy evaluation scales. Data were extracted， and the methodological quality and measurement properties of the included scales were assessed according to the consensus-based standards for the selection of health measurement instruments （COSMIN）. Recommendation levels were formulated based on the grading of evidence. ResultsA total of 46 studies were included， involving 22 generic syndrome efficacy evaluation scales and 24 disease-specific syndrome efficacy evaluation scales. None of the scales reported cross-cultural validity or measurement error. According to the recommendation grades， 2 scales met Grade A recommendations and are suggested for clinical use； 38 scales were classified as Grade B， indicating potential applicability but requiring further validation； and 6 scales were classified as Grade C， suggesting the need for further refinement. ConclusionExisting TCM syndrome efficacy evaluation scales exhibit substantial variability in methodological quality， incomplete reporting of measurement properties， and insufficient attention to scale revision. Future efforts should emphasize standardized design in the development of TCM syndrome scales， strengthen validation procedures for key measurement properties， and prioritize dynamic revision of scales， thereby providing high-quality tools to support the precise evaluation of syndrome efficacy.

Objective To provide basis for the formation of acute exacerbation of chronic obstructive pulmonary disease(AECOPD-STES),the item weight of the syndrome therapeutic evaluation scale for AECOPD-STES was determined.Methods Based on the clinical survey data of 387 AECOPD patients,the random forest method was adopted,and the Spyder integrated development environment.Anaconda navigator software was used to call the"random forest Classifier"in the sklearn package to establish the initial random forest model and calculate the item weights.Factor analysis was used to extract common factors with cumulative variance contribution>80%,and the item weight was calculated according to the cumulative variance contribution and component score coefficient of common factors.The percentage weight method was used to calculate the item weight based on the importance score of each item by 29 experts.Finally,40%,30%and 30%of the above three methods were given respectively to determine the final weight of the items.Results The random forest method showed that the weights of wind cold syndrome,cold Yin syndrome,phlegm heat syndrome,phlegm dampness syndrome and blood stasis syndrome were 0.014-0.170,0.076-0.194,0.017-0.183,0.010-0.183 and 0.069-0.298,respectively.Factor analysis showed that the weights of wind cold syndrome,cold yin Syndrome,phlegm heat syndrome,phlegm dampness syndrome and blood stasis syndrome were 0.030-0.111,0.100-0.182,0.037-0.095,0.022-0.141 and 0.054-0.185,respectively.The percentage weight method shows that the weight ranges of wind cold syndrome,cold yin Syndrome,phlegm heat syndrome,phlegm dampness syndrome and blood stasis syndrome were 0.072-0.102,0.146-0.182,0.057-0.077,0.075-0.111 and 0.115-0.185,respectively.According to the three methods,the weights of wind cold syndrome,cold yin Syndrome,phlegm heat syndrome,phlegm dampness syndrome and blood stasis syndrome were 0.050-0.121,0.117-0.174,0.040-0.117,0.056-0.130 and 0.092-0.188,respectively.Conclusion This study determined the weight of each item of AECOPD-STES,providing a basis for the calculation of syndrome score.

Bronchiectasis is one of the most common and refractory lower respiratory tract diseases in clinic practice.Pseudomonas aeruginosa is the most common frequently isolated pathogen in adults with bronchiectasis complicated by infection.The complex relationship among inflammation,immunity,infection and structural damage in the airway of patients has been described as a"vicious circle"model,but the specific mechanism of different pathological links in this model and their intricate interactions are still not fully understood.The theory of"Strengthening fire eating qi"first appeared in Su Wen·Yin Yang Ying Xiang Da Lun,and provides simply explain the"qi"damage to"shape"damage of patients'airway from the perspective of"fire"and"qi"in traditional Chinese medicine,and provide new ideas for explaining the pathological mechanism connotation of bronchiectasis combined with Pseudomonas aeruginosa infection.The exploration of pathological mechanism is the fundamental source of understanding disease progression and discovering new treatment ideas.At present,the clinical treatment of Western medicine for patients with bronchiectasis mainly focuses on anti-infection and symptomatic treatment.Although etiological targeted therapies and targeted drugs are constantly explored and developed,they are still rarely applied in clinical practice.As a treasure of Chinese culture,traditional Chinese medicine has the advantage of taking both specimens into consideration,and its clinical efficacy and pharmacological value are worthy of further study.Based on the classical theory of"Strengthening fire eating qi",this review aims to understand and summarize the modern pathological mechanism of bronchiectasis combined with Pseudomonas aeruginosa infection and highlights current research hotspots in both Chinese and Western medicine treatment,in order to provide clinical thinking.

Objective To explore the correlation between different syndromes of sepsis and laboratory parameters,SOFA score,and APACHE Ⅱ score,providing reference for improving the objectivity of traditional Chinese medicine syndrome differentiation.Methods Based on the cross-sectional survey,information of the four diagnostic methods of traditional Chinese medicine,laboratory parameters,and disease assessment scales were collected from sepsis patients admitted to ICUs in 8 hospitals across the country.ANOVA,non-parametric tests,and Logistic regression analysis were used to screen for sepsis syndrome related factors.Results A total of 905 sepsis patients were included,and the distributions of traditional Chinese medicine syndromes were as follows:163(18.01%)of phlegm heat obstructing the lungs syndrome,141(15.58%)of blood stasis and toxin obstruction(damage)syndrome,130(14.36%)of intense exuberant heat toxin syndrome,129(14.25%)of Yin exhaustion and Yang deficiency syndrome,124(13.70%)of Yangming fu-organ excess syndrome,96(10.61%)of lung Qi deficiency syndrome,68(7.51%)of Yin deficiency and internal heat syndrome,and 54(5.97%)of Qi and blood deficiency syndrome.The results of ANOVA and non-parametric tests showed that there were differences in 14 indicators,including body temperature,heart rate,WBC,NE%,PCT,CRP,PLT,D-D,APTT,Lac,HCT,Hb,SOFA score,APACHE Ⅱ score among 8 common syndromes(P<0.05);Using the 14 indicators mentioned above as independent variables,and syndrome as the dependent variable,Logistic regression analysis was conducted.The results showed that in the excess syndrome category:①Phlegm heat obstructing lung syndrome was positively correlated with heart rate and WBC,and negatively correlated with Lac and APACHE Ⅱ scores;②Intense exuberant heat toxin syndrome was positively correlated with body temperature,WBC,NE%,PCT,CRP,and negatively correlated with PLT and SOFA scores;③Yangming fu-organ excess syndrome was positively correlated with body temperature and negatively correlated with PCT;④Blood stasis and toxin obstruction(damage)syndrome was positively correlated with body temperature,NE%,PLT,CRP,and D-D,and negatively correlated with heart rate,WBC,PCT,and APTT.Deficiency syndrome category:①Lung Qi deficiency syndrome was positively correlated with Hb,and negatively correlated with body temperature,WBC,and HCT;②Yin deficiency and internal heat syndrome were negatively correlated with NE%and CRP;③Qi and blood deficiency syndrome was positively correlated with APACHE Ⅱ score,and negatively correlated with body temperature,Hb,PLT,D-D;④Yin exhaustion and Yang deficiency syndrome was positively correlated with heart rate,PCT,Lac,SOFA score,and APACHE Ⅱ score,and negatively correlated with body temperature.Conclusion Patients with sepsis with excess syndrome category have higher WBC,NE%,PCT,CRP scores,which suggests a drastic inflammatory response.Among them,Blood stasis and toxin obstruction(damage)syndrome have highest PLT,D-D,and lowest APTT,suggesting a more severe disorder of coagulation function.Deficiency syndrome category,especially patients with Yin exhaustion and Yang prostration syndrome has higher Lac and SOFA score and APACHE Ⅱ score than other patients with sepsis of other syndromes,suggesting a worse condition and poor prognosis.

Objective To provide basis for the formation of acute exacerbation of chronic obstructive pulmonary disease(AECOPD-STES),the item weight of the syndrome therapeutic evaluation scale for AECOPD-STES was determined.Methods Based on the clinical survey data of 387 AECOPD patients,the random forest method was adopted,and the Spyder integrated development environment.Anaconda navigator software was used to call the"random forest Classifier"in the sklearn package to establish the initial random forest model and calculate the item weights.Factor analysis was used to extract common factors with cumulative variance contribution>80%,and the item weight was calculated according to the cumulative variance contribution and component score coefficient of common factors.The percentage weight method was used to calculate the item weight based on the importance score of each item by 29 experts.Finally,40%,30%and 30%of the above three methods were given respectively to determine the final weight of the items.Results The random forest method showed that the weights of wind cold syndrome,cold Yin syndrome,phlegm heat syndrome,phlegm dampness syndrome and blood stasis syndrome were 0.014-0.170,0.076-0.194,0.017-0.183,0.010-0.183 and 0.069-0.298,respectively.Factor analysis showed that the weights of wind cold syndrome,cold yin Syndrome,phlegm heat syndrome,phlegm dampness syndrome and blood stasis syndrome were 0.030-0.111,0.100-0.182,0.037-0.095,0.022-0.141 and 0.054-0.185,respectively.The percentage weight method shows that the weight ranges of wind cold syndrome,cold yin Syndrome,phlegm heat syndrome,phlegm dampness syndrome and blood stasis syndrome were 0.072-0.102,0.146-0.182,0.057-0.077,0.075-0.111 and 0.115-0.185,respectively.According to the three methods,the weights of wind cold syndrome,cold yin Syndrome,phlegm heat syndrome,phlegm dampness syndrome and blood stasis syndrome were 0.050-0.121,0.117-0.174,0.040-0.117,0.056-0.130 and 0.092-0.188,respectively.Conclusion This study determined the weight of each item of AECOPD-STES,providing a basis for the calculation of syndrome score.

Objective To explore the correlation between different syndromes of sepsis and laboratory parameters,SOFA score,and APACHE Ⅱ score,providing reference for improving the objectivity of traditional Chinese medicine syndrome differentiation.Methods Based on the cross-sectional survey,information of the four diagnostic methods of traditional Chinese medicine,laboratory parameters,and disease assessment scales were collected from sepsis patients admitted to ICUs in 8 hospitals across the country.ANOVA,non-parametric tests,and Logistic regression analysis were used to screen for sepsis syndrome related factors.Results A total of 905 sepsis patients were included,and the distributions of traditional Chinese medicine syndromes were as follows:163(18.01%)of phlegm heat obstructing the lungs syndrome,141(15.58%)of blood stasis and toxin obstruction(damage)syndrome,130(14.36%)of intense exuberant heat toxin syndrome,129(14.25%)of Yin exhaustion and Yang deficiency syndrome,124(13.70%)of Yangming fu-organ excess syndrome,96(10.61%)of lung Qi deficiency syndrome,68(7.51%)of Yin deficiency and internal heat syndrome,and 54(5.97%)of Qi and blood deficiency syndrome.The results of ANOVA and non-parametric tests showed that there were differences in 14 indicators,including body temperature,heart rate,WBC,NE%,PCT,CRP,PLT,D-D,APTT,Lac,HCT,Hb,SOFA score,APACHE Ⅱ score among 8 common syndromes(P<0.05);Using the 14 indicators mentioned above as independent variables,and syndrome as the dependent variable,Logistic regression analysis was conducted.The results showed that in the excess syndrome category:①Phlegm heat obstructing lung syndrome was positively correlated with heart rate and WBC,and negatively correlated with Lac and APACHE Ⅱ scores;②Intense exuberant heat toxin syndrome was positively correlated with body temperature,WBC,NE%,PCT,CRP,and negatively correlated with PLT and SOFA scores;③Yangming fu-organ excess syndrome was positively correlated with body temperature and negatively correlated with PCT;④Blood stasis and toxin obstruction(damage)syndrome was positively correlated with body temperature,NE%,PLT,CRP,and D-D,and negatively correlated with heart rate,WBC,PCT,and APTT.Deficiency syndrome category:①Lung Qi deficiency syndrome was positively correlated with Hb,and negatively correlated with body temperature,WBC,and HCT;②Yin deficiency and internal heat syndrome were negatively correlated with NE%and CRP;③Qi and blood deficiency syndrome was positively correlated with APACHE Ⅱ score,and negatively correlated with body temperature,Hb,PLT,D-D;④Yin exhaustion and Yang deficiency syndrome was positively correlated with heart rate,PCT,Lac,SOFA score,and APACHE Ⅱ score,and negatively correlated with body temperature.Conclusion Patients with sepsis with excess syndrome category have higher WBC,NE%,PCT,CRP scores,which suggests a drastic inflammatory response.Among them,Blood stasis and toxin obstruction(damage)syndrome have highest PLT,D-D,and lowest APTT,suggesting a more severe disorder of coagulation function.Deficiency syndrome category,especially patients with Yin exhaustion and Yang prostration syndrome has higher Lac and SOFA score and APACHE Ⅱ score than other patients with sepsis of other syndromes,suggesting a worse condition and poor prognosis.

Bronchiectasis is one of the most common and refractory lower respiratory tract diseases in clinic practice.Pseudomonas aeruginosa is the most common frequently isolated pathogen in adults with bronchiectasis complicated by infection.The complex relationship among inflammation,immunity,infection and structural damage in the airway of patients has been described as a"vicious circle"model,but the specific mechanism of different pathological links in this model and their intricate interactions are still not fully understood.The theory of"Strengthening fire eating qi"first appeared in Su Wen·Yin Yang Ying Xiang Da Lun,and provides simply explain the"qi"damage to"shape"damage of patients'airway from the perspective of"fire"and"qi"in traditional Chinese medicine,and provide new ideas for explaining the pathological mechanism connotation of bronchiectasis combined with Pseudomonas aeruginosa infection.The exploration of pathological mechanism is the fundamental source of understanding disease progression and discovering new treatment ideas.At present,the clinical treatment of Western medicine for patients with bronchiectasis mainly focuses on anti-infection and symptomatic treatment.Although etiological targeted therapies and targeted drugs are constantly explored and developed,they are still rarely applied in clinical practice.As a treasure of Chinese culture,traditional Chinese medicine has the advantage of taking both specimens into consideration,and its clinical efficacy and pharmacological value are worthy of further study.Based on the classical theory of"Strengthening fire eating qi",this review aims to understand and summarize the modern pathological mechanism of bronchiectasis combined with Pseudomonas aeruginosa infection and highlights current research hotspots in both Chinese and Western medicine treatment,in order to provide clinical thinking.

ObjectiveTo explore the method of optimizing the performance of traditional Chinese medicine （TCM） syndrome diagnostic models using Stacking ensemble learning. MethodsTaking the construction of TCM syndrome diagnostic model for lung cancer as an example， 2598 cases of clinical symptoms and signs from lung cancer patients in 9 hospitals were used as independent variables （i.e.， feature variables）， TCM syndrome information as dependent variables， and the clinical data were divided into training set and testing set in 8：2 ratio according to random number table method using Python 3.7 software. The stable features of TCM syndrome of lung cancer were screened using chi-square test， Spearman's correlation test， and Least Absolute Shrinkage and Selection Operator （LASSO） logistic regression analysis； nine machine learning algorithms are trained， including support vector machines （SVMs）， k-nearest neighbors （KNN） algorithm， Random Forest （RF）， Extremely Randomized Trees， Extreme Gradient Boosting （XGBoost）， Lightweight Gradient Boosting （LightGBM）， Adaptive Boosting （AdaBoost）， Gradient Boosting （GB） and the multi-layer perceptron （MLP）， to obtain 9 basic models. Four models with better performance were screened out from the above basic models and fused to form a fusion model by using the Stacking ensemble learning， and the fusion model was trained twice by the above nine machine learning algorithms and evaluated by accuracy rate， micro-average ROC curves， area under the curve （AUC）， and confusion matrix metrics， to screen the optimal diagnostic model. ResultsAfter data processing， 79 stable features and 13 TCM syndromes were obtained. In the basic model training， the comprehensive performance of RF， ExtraTrees， MLP and SVM basic models were better， so the predicted distributions of the syndromes of these four models were used as the secondary training data， and nine fusion models were obtained based on the Stacking ensemble learning （SVM， KNN， RF， ExtraTree， XGBoost， LightGBM， GB， AdaBoost， MLP）. Among them， the XGBoost fusion model performed the best， with an accuracy of 0.850 and 0.838 in the training set and test set， respectively， an overfitting difference of 0.012， and an area under the micro-average ROC curve of 0.996. All fusion models showed an improvement in accuracy and area under the micro-average ROC curve compared with the base model in the test set. ConclusionTaking the TCM syndrome information of lung cancer as an example， the XGBoost fusion model has significant advantages in improving the diagnostic performance of TCM syndrome information of lung cancer through Stacking ensemble learning. It can be seen that the advantages of Stacking ensemble learning to integrate multiple models and effectively improve the diagnostic efficiency of TCM diagnostic models， which provided a methodological reference for similar studies.

Pituitary neuroendocrine tumors (PitNETs) are the second common central nervous system tumors. Patients often present with headache, vision loss, visual field defects, and cognitive dysfunction. Cognitive function is the ability of the brain to acquire, analyze and process external information; once the patient has serious cognitive dysfunction, it will bring heavy burden to the family and society. This article summarizes the cognitive functions in patients with PitNETs from perspectives of hormone, anatomical structures around the pituitary, tumor volume, treatment, and cognitive function assessment, in order to provide research ideas in elucidating relevant mechanisms in the future and provide basis for formulating rehabilitation plans for patients.

【Objective】 To investigate the practice and benefit of national standardized management of type 2 diabetes in Yulin City. 【Methods】 We recruited the adult type 2 diabetes patients who sought medical help at our hospital from May 2020 to October 2022 as subjects. We collected their basic information (sex and age); measured height, weight, waist and hip circumference, and blood pressure; calculated body mass index (BMI); and detected blood glucose, c-peptide, HbA1c, biomarkers, urinary microalbumin, sensory nerve conduction velocity of lower limbs, ABI, and subcutaneous and visceral fat at the time of MMC recruited and the end of six months. T test and Mann-Whitney U rank sum test were used for measurement data and χ² test or Fisher’s exact probability method for counting data to analyze the data. 【Results】 After 6 months, the levels of fasting blood glucose, postprandial blood glucose, HbA1c, and visceral and subcutaneous fat in all the patients decreased, but the level of fasting c-peptide increased compared with the baseline (all P<0.05). Secondly, compared with the baseline, the control rate of HbA1c (35.21% vs. 13.71% ) and the comprehensive control rate (13.97% vs. 7.26% ) were both significantly increased at six months (P<0.05). Thirdly, after 6 months, the levels of fasting blood glucose, postprandial blood glucose, HbA1c, TG, TC, and UA were decreased more, while the fasting c-peptide and postprandial c-peptide were increased more in the patients of the HbA1c standard group (HbA1c<7% ) than those of the non-standard group. 【Conclusion】 The multiple benefits of blood glucose, blood lipid, uric acid and islet function can be achieved by taking type 2 diabetes patients into MMC. Meanwhile, the rates of HbA1c control and comprehensively reaching the standard are significantly increased. Therefore, MMC can explore a new way for the management of type 2 diabetic patients in this area.