OBJECTIVE To evaluate the efficacy and safety of immune checkpoint inhibitors （ICIs） combined with neoadjuvant chemotherapy in the treatment of early triple-negative breast cancer （TNBC）. METHODS Randomized controlled trials （RCTs） comparing ICIs combined with neoadjuvant chemotherapy （experimental group） versus neoadjuvant chemotherapy alone （control group） were retrieved from PubMed， Cochrane Library， Embase， Web of Science， CNKI， Wanfang Data， and VIP databases， as well as relevant studies published at oncology academic conferences. The search period was from database inception to June 30， 2025. After literature screening， data extraction， and quality assessment， a meta-analysis was performed by using RevMan 5.4 software. RESULTS A total of 6 RCTs involving 3 786 patients were finally included. The meta-analysis results showed that the experimental group had superior event-free survival [HR＝0.73， 95%CI （0.62， 0.85）， P＜0.000 1]， overall survival [HR＝0.69， 95%CI （0.57， 0.84）， P＝0.000 3]， and pathological complete response （pCR） [OR＝1.57， 95%CI （1.37， 1.80）， P＜0.000 01] compared to the control group. The incidence of ≥grade 3 adverse event （AE）， severe AE （SAE）， and ≥ grade 3 immune-related adverse event （irAE） in the experimental group was significantly higher than that in the control group. There was no statistically significant difference between the two groups in the incidence of any AE or any irAE （P＞0.05）. Subgroup analysis revealed that， regardless of programmed cell death ligand 1 expression status （negative or positive），the pCR in the experimental group was significantly higher than that in the control group （P＜0.05）. Additionally， the pCR of the patients with positive lymph nodes in the experimental group was significantly higher to that in the ontrol group （P＜0.05）. There was no statistically significant difference in pCR between the two groups with negative lymph nodes （P＝0.09）. CONCLUSIONS ICIs combined with neoadjuvant chemotherapy can significantly improve event-free survival and overall survival in patients with TNBC， providing patients with long-term survival benefits. However， the risk of ≥ grade 3 AE， SAE and ≥ grade 3 irAE has increased.

Objective To investigate the key factors influencing the willingness of chronic disease patients to participate in home pharmaceutical services.Methods The study adopted the data from inner Mongolia and northeast China set of the drug aging system research for China.The Null Importance method was employed to identify key factors influencing the willingness of chronic disease patients to participate in home pharmaceutical services.The logistic regression model was constructed and evaluated the impact of feature selection through 5 fold cross-validation and accuracy and AUC values.Results 10 key factors were selected by the Null Importance method and the performance of the logistic regression model was improved after feature selection.The factors which significantly affected patients' willingness to accept home pharmaceutical services included the number of accessible information sources(OR=1.261,95％CI=1.182～1.345),medication therapeutic indication cognition(OR=1.342,95％CI=1.124～1.603),the presence the drug packaging or not(OR=1.218,95％CI=1.015～1.462),medication adherence(OR=0.881,95％CI=0.839～0.925),medication literacy(OR=0.631,95％CI=0.488～0.817),the degree of know of medication guidance services(OR=1.211,95％CI=1.017～1.442).Conclusion The logistic model refined by the Null Importance feature selection method demonstrated good performance and was conducive to analyzing the factors influencing the willingness of chronic disease patients to participate in home pharmaceutical care.

OBJECTIVE To construct a predictive tool for surgical site infections(SSIs)in spinal surgery for Chi-nese population to provide evidence support for reducing SSIs.METHODS A systematic review of Chinese and English database literature was conducted for Meta-analysis to obtain pooled risk values for influencing factors,and a risk prediction scoring tool was constructed based on the logistic regression model.Patients who underwent spinal surgery and completed postoperative follow-up in a tertiary hospital in Beijing from Jan.to Dec.2021 were selected to validate the predictive effect of the tool.RESULTS The predictive model for SSIs in Chinese spinal sur-gery patients was Logit(P)=—3.47+0.63(age 60 years)+0.31 ×(patient with cardiovascular disease)+0.69 ×(rheumatoid arthritis)+1.07 ×(diabetes)+1.06 ×(operation duration＞3 h)+1.17 ×(preopera-tive albumin＜35 g/L)+0.71 ×(history of spinal surgery)+0.67 ×(carrying internal implants)+0.73 ×(blood transfusion).The total score of the predictive tool was 92,with a cutoff score of≥24.50 indicating high-risk individuals.The area under the curve was 0.733,with the sensitivity 58.30％and the specificity 79.60％.CONCLUSION The established predictive model for SSIs in Chinese spine surgery demonstrates good predictive performance and can be used as a reference assessment tool in clinical practice.

Objective To evaluate the efficacy,safety and cost-effectiveness of dorzagliatin in the treatment of type 2 diabetes mellitus using a rapid health technology assessment,and to provide medical evidence for clinical decision-making.Methods PubMed,Embase,Cochrane Library,CNKI,Wanfang Data,SinoMed and relevant health technology assessment(HTA)websites and databases were searched to collect systematic reviews/Meta-analysis,pharmacoeconomic literature and HTA reports of dorzagliatin in the treatment of type 2 diabetes from inception to July 20,2024.Two reviewers independently screened literature,extracted date and assessed quality.The results were qualitatively described and analyzed.Results A total of 6 studies were included,including 5 systematic reviews/Meta-analysis and a pharmacoeconomic study.In terms of efficacy compared with placebo,dorzagliatin significantly reduced glycated hemoglobin(HbA1c),fasting plasma glucose,2-hour postprandial blood glucose and insulin resistance index(P＜0.05),improved HbA1c compliance rate in terms of safety,dorzagliatin,and enhanced homeostasis model assessment-β(P＜0.05),significantly increased total cholesterol,triglyceride,body weight and body mass index(P＜0.05).In terms of safety,the total incidence of adverse reactions of dorzagliatin was slightly higher than that of the placebo group(P＜0.05).However,there was no significant difference in the incidence of severe adverse reactions between the two groups(P＞0.05),and there was no significant increase in the incidence of hyperlipidemia and hypoglycemia(P＞0.05).In terms of economy,the treatment of dorzagliatin combined with metformin has a long-term cost-utility advantage,with an economic probability of nearly 70％.Conclusion Compared with placebo,dorzagliatin has a good overall efficacy and safety in the treatment of type 2 diabetes.In terms of safety,the total incidence of adverse reactions of dorzagliatin was slightly higher than that of placebo.In terms of economy,compared with metformin alone,dorzagliatin combined with metformin has economic advantages.However,there is a lack of head-to-head comparisons of doxorubicin with other classes of glucose-lowering medications,and none of the included studies described long-term cardiac,cerebral,or renal benefits,which limits the comprehensive evaluation of the efficacy and safety of dorzagliatin.

OBJECTIVE To assess the current status of hospital-acquired infections and their economic burden in or-thopedic patients based on diagnosis-related groups(DRG).METHOD Based on the National Health Insurance dis-ease diagnosis-related groups,32 413 orthopedic patients from a tertiary care hospital in Beijing in 2021 were grouped,hospital-acquired infections were retrospectively analyzed,and the direct and indirect economic burdens of different DRG groups were assess using indictors such as hospitalization time and cost,bed turnover loss,and labor time loss.RESULTS A total of 32 413 patients were included,the incidence of hospital-acquired infection was 0.47％(153/32 413),the site of infection was predominantly the surgical site(57.99％),and hospital-acquired infections in the hematologic system had a greater impact on cost-consumption indices and time-consumption indi-ces.The infection cases were concentrated in 19.58％of the DRGs groups.The IF23 group(lower limb bone sur-gery with complications and comorbidities)had the highest direct economic burden(24 010 yuan/case)due to hos-pital-acquired infections,and the increase in the cost of consumables and medication was the main factor causing the direct economic burden.At both the hospital level and family-society level,the top three DRG groups in terms of indirect economic burden due to hospital-acquired infections were IB15,IB13 and IF23.CONCLUSION Hospital-acquired infections in orthopedic patients have a tendency to be concentrated,quantitatively assessment of their e-conomic burden based on DRGs not only illustrates the importance of hospital-acquired infection prevention and control,but also accurately identifies the disease groups that require focused management,providing an evidence-based basis for precise prevention and control of hospital-acquired infections.

Objective To screen and identify significant influencing factors associated with voriconazole clearance using machine learning algorithms.Methods This study utilized a clinical dataset of elderly patients undergoing voriconazole treatment at our institution.We employed seven feature selection techniques from three categories of methods(filter,wrapper methodsand Embedded methods)to identify crucial influencing factors related to voriconazole clearance.Then six algorithms including Stochastic Gradient Descent Regression(SGDR),Lasso Regression(LassoR),Ridge Regression(RidgeR),Random Forest Regression(RFR),XGBoost Regression(XGBR),and Support Vector Regression(SVR),were applied to identify the best models by 5 fold cross-validation and the mean absolute error.SHAP values were employed to analyze the importance of influencing factors.Results The SVR model outperformed other regressors and were considered.The model was developed for seven selected features,which demonstrated good precision with an average relative error was 32.57%,and with approximately 57.89%of predicted values falling within a relative error range of±20%.The SHAP results revealed the importance ranking of influencing factors as ALT,ALP,PLT,administration method,CREA,TBIL,and PCT.Conclusion Feature selection techniques applied in machine learning can be utilized for the screening of influencing factors linked to voriconazole clearance.

Objective To investigate the key factors influencing the willingness of chronic disease patients to participate in home pharmaceutical services.Methods The study adopted the data from inner Mongolia and northeast China set of the drug aging system research for China.The Null Importance method was employed to identify key factors influencing the willingness of chronic disease patients to participate in home pharmaceutical services.The logistic regression model was constructed and evaluated the impact of feature selection through 5 fold cross-validation and accuracy and AUC values.Results 10 key factors were selected by the Null Importance method and the performance of the logistic regression model was improved after feature selection.The factors which significantly affected patients' willingness to accept home pharmaceutical services included the number of accessible information sources(OR=1.261,95％CI=1.182～1.345),medication therapeutic indication cognition(OR=1.342,95％CI=1.124～1.603),the presence the drug packaging or not(OR=1.218,95％CI=1.015～1.462),medication adherence(OR=0.881,95％CI=0.839～0.925),medication literacy(OR=0.631,95％CI=0.488～0.817),the degree of know of medication guidance services(OR=1.211,95％CI=1.017～1.442).Conclusion The logistic model refined by the Null Importance feature selection method demonstrated good performance and was conducive to analyzing the factors influencing the willingness of chronic disease patients to participate in home pharmaceutical care.

Objective To explore the risk factors for vancomycin-related acute kidney injury(VA-AKI)in elderly patients.Methods Clinical data of elderly inpatients who used vancomycin at the Inner Mongolia Autonomous Region People's Hospital from January 2021 to June 2024 were retrospectively collected.The incidence of VA-AKI and the situation of treatment drug monitoring(TDM)were statistically analyzed.LASSO regression was used for feature selection,and this process was repeated 10,000 times.In each iteration,75％of the training samples were randomly selected,and the frequency of each feature being selected was counted.Finally,the features with higher frequency in multiple iterations were selected for model training.The data were divided into training set and test set at an 8∶2 ratio.Four machine learning prediction models,including Logistic regression,random forest,extreme gradient boosting(XGBoost),and support vector machine(SVM),were established.The accuracy and area under the receiver operating characteristic curve(AUC)of the above prediction models were calculated in the test set.The minimum depth distribution was used to visualize the importance of the characteristics of the model.Results A total of 305 elderly patients receiving vancomycin were included,among which 49 cases(16.07％)developed VA-AKI.LASSO regression analysis selected 7 characteristic variables to build 4 machine learning models,and finally selected the random forest model as the risk prediction model.The random forest model has an AUC value of 0.91,an accuracy of 0.89,an accuracy of 0.88,a recall rate of 0.98,and an F1 value of 0.93.The predictor importance ranking was in order of post-treatment creatinine level,C-reactive protein(CRP),albumin(Alb),respiratory failure,cardiac insufficiency,trough concentration time,and dose.Conclusion Post-treatment creatinine level,respiratory weakness,trough concentration time,cardiac insufficiency,Alb,CRP,and dosage were the risk factors for VA-AKI.The random forest model is the most effective in predicting the risk of VA-AKI in elderly patients,providing a reference for rational use of vancomycin in elderly patients.

Objective To evaluate the safety and efficacy of ciprofol in the anesthesia of elderly patients undergoing bronchoscopy.Methods A total of 96 elderly patients(≥65 years old)undergoing fiberoptic bronchos-copy under sedation and anesthesia were randomly assigned to either the ciprofol group(Group C,n=48)or the propofol group(Group P,n=48).In Group C,anesthesia was induced with an intravenous injection of sufentanil at 0.1 μg/kg and ciprofol at 0.3 mg/kg.In Group P,anesthesia was induced with an intravenous injection of sufent-anil at 0.1 μg/kg and propofol medium/long-chain fat emulsion at 1.5 mg/kg.Hemodynamic parameters,including heart rate(HR),mean arterial pressure(MAP),and peripheral oxygen saturation(SpO2),were recorded at five time points:before anesthesia induction(T1),immediately after the bronchoscope passed through the glottis(T2),immediately after it reached the carina(T3),immediately after the bronchoscope was withdrawn from the nostril post-procedure(T4),and upon full consciousness after leaving the recovery room(T5).Additionally,the success rate of sedation and anesthesia,cough severity scores,induction time(t1),bronchoscopy duration(t2),recovery time(t3),and orientation recovery time(t4)were documented for both groups.Intraoperative complications,such as hypotension,hypoxemia(SpO2<90%),injection pain during induction,airway interventions(e.g.,jaw support,mask ventilation),and the number of additional sedative doses administered,were also recorded.Results Compared with T1,MAP in both groups decreased at T2 and T3(P<0.05).Compared with group P,group C exhibited a higher MAP at T2 and T3(P<0.05).between the two groups in terms of sedation success rate,induction time,cough score,examination time,recovery time,and orientation recovery time(P>0.05).Compared with group P,group C demonstrated lower incidences of hypotension,hypoxemia,injection pain,and fewer airway intervention events(P<0.05).Conclusions Compared with propofol,ciprofol in combination with sufentanil demonstrates superior circulatory stability,a lower incidence of respiratory system-related adverse reactions,and reduced injection pain.Therefore,it can be safely and effectively utilized for painless bronchoscopic diagnosis and treatment in elderly patients.

Microbial-derived metabolites are important mediators of host-microbial interactions. In recent years, the role of intestinal microbial metabolites in colorectal cancer has attracted considerable attention. These metabolites, which can be derived from bacterial metabolism of dietary substrates, modification of host molecules such as bile acids, or directly from bacteria, strongly influence the progression of colitis-associated cancer (CAC) by regulating inflammation and immune response. Here, we review how microbiome metabolites short-chain fatty acids (SCFAs), secondary bile acids, polyamines, microbial tryptophan metabolites, and polyphenols are involved in the tumorigenesis and development of CAC through inflammation and immunity. Given the heated debate on the metabolites of microbiota in maintaining gut homeostasis, serving as tumor molecular markers, and affecting the efficacy of immune checkpoint inhibitors in recent years, strategies for the prevention and treatment of CAC by targeting intestinal microbial metabolites are also discussed in this review.
Humans ; Gastrointestinal Microbiome/physiology* ; Animals ; Carcinogenesis/metabolism* ; Colitis-Associated Neoplasms/microbiology* ; Fatty Acids, Volatile/metabolism* ; Bile Acids and Salts/metabolism* ; Colitis/microbiology*