Objective To summarize experience of anti-cancer drug management for clinical trials,and to explore a more efficient and standardized management model of anti-cancer drugs used in clinical trials.Methods Based on our current work in central pharmacy,the particularity and complexity of anti-cancer drug management for clinical trials were analyzed.In the meantime,we identified high-risk parts in the drug management process.Based on those risks,feasible measures were taken and presented in detail.Results Management of anti-cancer drugs used in clinical trials has its characteristics,such as long cycle,low error-tolerant rate,closed-loop model,etc.Recognizing these representative high-risk parts during the trials and making responses,including standardization of drug management records and disposition of drugs and packaging returned by subjects,should be achieved as soon as possible.Conclusion Establishing and observing strict rules and regulations,improving the hardware and software performance of the central pharmacy as well as implementing risk-based drug management is beneficial to conduct clinical trials normatively.

OBJECTIVE To construct a prediction model of mild cognitive impairment(MCI)in elderly patients with hyperten-sion based on the bi-dimensional features of Chinese and western medicine with the help of machine learning(ML).METHODS The clinical data of 502 patients over 60 years old with essential hypertension treated in hospital from January 2020 to March 2023 were collected and analyzed,randomly divided into training set and verification set according to a ratio of 7∶3,and divided into cognitive impairment group(n=104)and cognitive normal group(n=398).LASSO regression analysis was used to reduce the dimension of clin-ical indicator data and screen out the core predictors.Six ML algorithms,logistic regression,XGBoost,AdaBoost,SVM,GNB,and MLP were used to construct the models,and ROC curves were plotted to compare the AUC,accuracy,sensitivity,specificity,and F1 scores of the 6 models.SHAP models were adopted to reveal the characteristic importance of predictors.RESULTS Waist-hip ratio,qi depression,age,total cholesterol,phlegm-dampness,damp-heat,qi deficiency and fasting blood glucose were the core predictors of early MCI in elderly hypertensive patients.The AUC,accuracy,sensitivity,specificity,and F1 scores of the XGBoost model were 0.938,0.885,0.846,0.896,and 0.755 respectively,which were superior to those of other algorithmic models.CONCLUSION The XGBoost model constructed on the basis of waist-to-hip ratio,qi depression,age,total cholesterol,phlegm-dampness,damp-heat,qi deficiency and fasting blood glucose has the best prediction performance,which can provide a reference basis for early identifi-cation of MCI risk and diagnostic and therapeutic decision-making in the clinical elderly hypertensive population.

OBJECTIVE To construct a prediction model of mild cognitive impairment(MCI)in elderly patients with hyperten-sion based on the bi-dimensional features of Chinese and western medicine with the help of machine learning(ML).METHODS The clinical data of 502 patients over 60 years old with essential hypertension treated in hospital from January 2020 to March 2023 were collected and analyzed,randomly divided into training set and verification set according to a ratio of 7∶3,and divided into cognitive impairment group(n=104)and cognitive normal group(n=398).LASSO regression analysis was used to reduce the dimension of clin-ical indicator data and screen out the core predictors.Six ML algorithms,logistic regression,XGBoost,AdaBoost,SVM,GNB,and MLP were used to construct the models,and ROC curves were plotted to compare the AUC,accuracy,sensitivity,specificity,and F1 scores of the 6 models.SHAP models were adopted to reveal the characteristic importance of predictors.RESULTS Waist-hip ratio,qi depression,age,total cholesterol,phlegm-dampness,damp-heat,qi deficiency and fasting blood glucose were the core predictors of early MCI in elderly hypertensive patients.The AUC,accuracy,sensitivity,specificity,and F1 scores of the XGBoost model were 0.938,0.885,0.846,0.896,and 0.755 respectively,which were superior to those of other algorithmic models.CONCLUSION The XGBoost model constructed on the basis of waist-to-hip ratio,qi depression,age,total cholesterol,phlegm-dampness,damp-heat,qi deficiency and fasting blood glucose has the best prediction performance,which can provide a reference basis for early identifi-cation of MCI risk and diagnostic and therapeutic decision-making in the clinical elderly hypertensive population.

【Objective】 To investigate the causes of intravenous malposition of double J stent and treatment strategies, in order to improve clinicians’ awareness of this complication. 【Methods】 Clinical data of a patient with intravenous malposition of double J stent were analyzed and relevant literature was reviewed. 【Results】 A 51-year-old female was admitted with post-hysterectomy urinary fistula and diagnosed with right intravenous malposition of double J stent and ureterovaginal fistula. Da Vinci robot-assisted laparoscopic right double J stent removal and ureteral reimplantation were performed. 【Conclusion】 Intravenous malposition is a rare and life threatening complication of double J stent placement, which can migrate further. The surgical method should be selected according to the location of the stent and general condition of the patients. Minimally invasive surgery is the first choice of treatment.

Objective:To investigate the relationship between fragment size of ulnar coronoid process fracture and patient prognosis.Methods:A retrospective study was conducted of the 34 patients who had been treated at Department of Orthopaedics, The Second Hospital Affiliated to Lanzhou University for fracture of ulnar coronoid process combined with elbow dislocation from July 2016 to December 2020. They were assigned into 2 groups according to their different treatments. In the surgery (internal fixation) group of 23 cases, there were 15 males and 8 females, aged from 22 to 71 years; in the conservative treatment group of 11 cases, there were 8 males and 3 females, aged from 38 to 78 years. Preoperatively, the sizes of coronoid process and fracture fragments were measured by elbow CT scan and 3D reconstruction, and a size-weighted ratio Z (%) corresponding to the fragment of coronoid process fracture was calculated. At the last follow-up, American Hospital for Special Surgery total elbow scoring system (HSS2) score was used to assess their therapeutic efficacy, the correlation between the ratio Z and HSS2 score for elbow function was calculated, and complications were recorded.Results:There were no significant differences between the surgery and conservative treatment groups in gender or age ( P>0.05). All the 34 patients were followed up for 18 to 54 months (average, 36.7 months). At the last follow-up, the HSS2 score was 93.77±0.84 (from 82 to 98) for the surgery group and 86.00±1.42 (from 78 to 90) for the conservative treatment group; the complications rate was 13.04% (3/23) for the former and 63.64% (7/11) for the latter. There was a linear relationship between the size-weighted ratio Z of the coronoid fracture fragment and the HSS2 elbow function score in the surgery group ( P<0.01). The linear regression equation between them was: y=99.44-0.121x ( r2=0.86, P<0.01). There was a linear relationship between the size-weighted ratio Z of the coronoid fracture fragment and the HSS2 elbow function score in the conservative treatment group ( P<0.01). The linear regression equation between them was: y=89.46-0.144x ( r2=-0.91, P<0.01). When a HSS2 elbow joint function score 90 was substituted into both linear regression equations, the results were x=78.02 for the surgery group and x=3.75 for the conservative treatment group. Conclusions:Conservative treatment may not lead to a satisfactory prognosis for the patients with coronoid process fracture whose size-weighted ratio of fracture fragment is larger than 3.75. Open reduction and internal fixation usually leads to a satisfactory prognosis for those whose size-weighted ratio of fracture fragment is smaller than 78.02.

Objective The role of this essay is to explore the relationship of BIM deletion polymorphism and paclitaxel intrinsic resistance in breast cancer. Methods Human breast cancer cell lines were screened by techniques of PCR and gene sequencing to detect BIM deletion polymorphism.MTS was used to detect the cytotoxic effects of paclitaxel in different cell lines. Meanwhile,levels of BIM mRNA and protein were detected by rtPCR and Western Blot. Results Comparing with the wild type cell line(MCF7),T47D was a deletion cell line with BIM deletion polymorphism and resistant to paclitaxel(T47D vs.MCF-7,IC50>30le vs.IC50=0.16 vs.02 μmol/L). Moreover,the ratio of BIM EXON3 to EXON4 was significantly increased and the level of functional BIM protein was down-regulated in T47D compared with MCF7(P < 0.05). Conclusion BIM deletion polymorphism might initiate intrinsic resistance to paclitaxel therapy in breast cancer.