To effectively introduce and utilize global advanced educational resources, the implementation of Chinese-foreign joint education program in medical universities and the establishment of an internal quality assurance system with Chinese characteristics and substantially equivalent to international standards of medical education is crucial for improving the quality of Chinese medical talent cultivation and achieving high-quality development of education opening up to the outside world in the new era. Using the Chinese-Foreign Joint Education Program jointly run by Chongqing Medical University and University of Leicester as an example, this paper proposes a plan for the development of an internal quality assurance system with three core indicators of management mechanism, team building, and student services. This plan provides experience and a reference for domestic universities to carry out cross-border medical education and improve the quality and efficiency of Chinese-foreign joint education programs.

Objective:To design an electronic nose that can detect and identify urinary volatile organic compounds (VOCs) as marker gases for bladder cancer.Methods:Isopropyl alcohol, ethylbenzene, acetic acid, and ammonia were selected as target gases, and 8 metal oxide gas sensors were used to construct sensor arrays for testing and collecting experimental data, and different characteristics were normalized. Recursive feature elimination (RFE) was used to select the best feature subset, and principal component analysis (PCA) and linear discriminant analysis (LDA) were further introduced to reduce the data dimension and facilitate visual analysis. In addition, three machine learning algorithms, including support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN), were combined to train and verify the model.Results:When the feature number was 12, the accuracy of the model classification had the best performance. The feature subset consisted of 5 differences, 5 sensitivities, and 2 integrals, and the data was reduced to 12 dimensions. Only PCA couldn’t distinguish the four gases. The LDA classification performance was significantly better than that of PCA, except that isopropyl alcohol and acetic acid had a small overlap area. LDA could distinguish ethylbenzene and ammonia from isopropyl alcohol and acetic acid; the sample points were gathered, which means the clustering performance was also better. The prediction accuracy of SVM, RF, and KNN was 0.85, 0.56, and 0.79, respectively. After model verification, the classification accuracy of PCA+SVM, LDA+RF, and LDA+KNN was 0.97, 0.94, and 0.97, respectively.Conclusions:An electronic nose was designed to detect and identify urinary VOCs marker gases for bladder cancer.

Objective:To summarize the best evidence for the management of lower urinary tract dysfunction (LUTD) in total hysterectomy patients, so as to provide evidence-based basis for clinical practice.Methods:According to the "6S" pyramid model, literature related to the management of LUTD in total hysterectomy patients was successively searched from guide websites, evidence-based websites, professional websites and comprehensive databases. The search deadline was from the establishment of the databases to March 31, 2023. Two researchers evaluated the quality of the included literature, extracted evidence and recommended the level of evidence.Results:A total of 14 articles were included, including one clinical decision, two evidence summaries, three guidelines, one expert consensus and seven systematic evaluations. A total of 25 pieces of evidence were summarized from four aspects, such as symptom assessment, urinary tract management, symptom intervention and health education.Conclusions:Medical staff should manage lower urinary tract dysfunction in patients undergoing total hysterectomy based on evidence-based evidence to prevent or reduce the occurrence of lower urinary tract dysfunction in patients.

Objective:To explore the different categories of family resilience in cervical cancer patients and their influencing factors.Methods:From October 2022 to September 2023, 275 cervical cancer patients admitted to the First Hospital of Shanxi Medical University were selected as the study subject by convenience sampling. Cervical cancer patients were surveyed using the self-made General Information Questionnaire, Benefit Finding Scale (BFS), Connor-Davidson Resilience Scale (CD-RISC), and shortened Chinese Version of the Family Resilience Assessment Scale (FRAS-C). Latent profile analysis was used to investigate the family resilience of patients, and Logistic regression was used to analyze the influencing factors of family resilience in different categories.Results:A total of 275 questionnaires were distributed, and 253 valid questionnaires were collected, with a valid response rate of 92.0% (253/275). Family resilience of cervical cancer patients was divided into three categories of low resilience-negative coping group (18.6%, 47/253), moderate resilience-communication disorder group (59.3%, 150/253), and high resilience-inclusive understanding group (22.1%, 56/253). The per capita family monthly income, place of residence, primary caregivers, whether to undergo radiotherapy or chemotherapy, psychological resilience, and disease benefit finding were the influencing factors of family resilience in different categories of cervical cancer patients ( P<0.05) . Conclusions:The family resilience of cervical cancer patients can be divided into three latent categories. Medical and nursing staff should identify the characteristics of different categories of patients and provide targeted intervention measures to improve their family resilience.

Objective To evaluate the perioperative safety and feasibility of day-case transurethral holmium laser enucleation of prostate(HoLEP)under over-night mode.Method From January 2021 to March 2023,83 patients of benign prostatic hyperplasia(BPH)were elected and treated with HoLEP by the one surgeon.According to different management methods,these patients were divided into the over-night day-case HoLEP group and the ordinary HoLEP group.Again,these patients were divided into large volume(≥50 mL)group and small volume(<50 mL)group according to the prostate volume.Record the age and perioperative data of all patients[total prostate volume,prostate resection weight,proportion of prostate resection,operating time,changes in peripheral venous blood hemoglobin(Hb),bladder flushing duration,catheter insertion duration,and success rate of first tube removal],the parameters of each group were compared.Result All of the 83 patients undergoing HoLEP surgery in this study,and there were no cases of HoLEP related reoperation or readmission.Among them,there were 43 cases in the over-night HoLEP group,aged 57～90 with an average of(70.1±7.3)years old,and the prostate volume was 29～161 mL with an average of(63.0±28.8)mL,All of them were discharged within 24 h,and there were no cases transferred to the ordinary HoLEP group,the success rate of first tube removal was 88.4%(38/43),and with average catheterization duration was(17.8±3.6)h;The other 40 cases were included into the ordinary HoLEP group,aged 55～87 with an average of(70.4±8.2)years old,the volume of the prostate was 22～118 mL with an average of(59.4±29.0)mL,the success rate of first tube removal was 90.0%(36/40),and with average catheterization duration was(77.5±25.1)h;There was no statistically significant difference in the perioperative parameters(total prostate volume,prostate resection weight,proportion of prostate resection,operating time,changes in peripheral venous blood Hb,and bladder flushing time)between the two groups(P>0.05),while the difference in catheter duration was statistically significant(P<0.01).Conclusion Regardless of the size of the prostate volume,day-case HoLEP is safe and feasible.Day-case HoLEP under the over-night mode is suitable for widespread and routine implementation in China,especially in medical centers with rich experience of HoLEP.

Objective This study aims to analyze the factors influencing benefit finding among cervical cancer patients and their spouses,as well as the interconnections between these factors.The goal is to provide a foundation for developing targeted clinical interventions.Methods Using the convenience sampling method,cervical cancer patients and spouses of 245 pairs who attended or were hospitalized in a tertiary-level hospital in Taiyuan City from October 2022 to July 2023 were selected as study subjects.Data were collected using a general information questionnaire,the Distress Disclosure Index,the Connor-Davidson Resilience Scale,and the Benefit Finding Scale.Univariate analysis,Pearson correlation analysis,and multiple linear regression were employed to scrutinize the data,leading to the establishment of Actor-Partner Interdependence Model.Results Benefit finding scores for cervical cancer patients and their spouses were(65.31±7.94)and(69.87±9.63),respectively.Multiple linear regression revealed that the educational level of patients and their spouses,whether or not they received chemotherapy or radiotherapy,self-disclosure and psychological resilience were the factors that affected patients'benefit finding.Spouse's education level,occupation,self-disclosure,psychological resilience and patients'self-disclosure and psychological resilience were the influencing factors of spouse's benefit finding.The Actor-Partner Interdependence Model analysis indicated that the self-disclosure and psychological resilience of cervical cancer patients positively predicted their own benefit finding and that of their spouses(path coefficients were 0.415,0.501,0.216,and 0.168,respectively,all P＜0.05).However,spouses'self-disclosure and psychological resilience could only positively predict their own benefit finding(path coefficients were 0.188 and 0.254,respectively,all P＜0.05).Conclusion Benefit finding among cervical cancer patients and their spouses is moderate and influenced by various factors.Both self-disclosure and psychological resilience of cervical cancer patients and their spouses have positive subjective effects on their own benefit finding.Healthcare professionals should encourage both parties to engage in healthy interactions about the disease,take steps to increase the level of psychological resilience of both,and ultimately tap into a higher level of benefit finding.

Objective To systematically review the risk prediction models for intradialytic hypotension in maintenance hemodialysis patients,with a view to provide references for clinical practice.Methods PubMed,Embase,Web of Science,Cochrane Library,CINAHL,CNKI,VIP,Wanfang and CBM were searched from inception to May 29,2023.2 reviewers independently screened the literature,extracted information and assessed methodological quality using the Prediction Model Risk of Bias Assessment Tool.Results A total of 20 studies and 25 models were included with the sample size of 68～9 292 cases and the incidence of outcome events of 2.1～51％.Baseline systolic blood pressure,age,ultrafiltration rate,diabetes and dialysis duration were the top 5 predictors of repeated reporting of the models.20 models reported the area under the curve of ranging from 0.649 to 0.969,and 5 models reported calibration metrics.There were 9 internal validations and 4 combined internal and external validation models.The overall applicability of the 20 studies was good,but all had a high risk of bias,mainly in data analysis.Conclusion Research on risk prediction models for intradialytic hypotension in maintenance hemodialysis patients is still in the developmental stage.Future studies should improve the research design and reporting process,and validation studies of existing models should be carried out to further evaluate the effectiveness and feasibility in clinical practice.

To analyze the factors affecting the cost of hospitalization for patients and provide insights using the intrauterine lesion surgery group (DRG code NE19) as an example.

BACKGROUND:Sepsis is one of the main causes of mortality in intensive care units(ICUs).Early prediction is critical for reducing injury.As approximately 36%of sepsis occur within 24 h after emergency department(ED)admission in Medical Information Mart for Intensive Care(MIMIC-IV),a prediction system for the ED triage stage would be helpful.Previous methods such as the quick Sequential Organ Failure Assessment(qSOFA)are more suitable for screening than for prediction in the ED,and we aimed to find a light-weight,convenient prediction method through machine learning. METHODS:We accessed the MIMIC-IV for sepsis patient data in the EDs.Our dataset comprised demographic information,vital signs,and synthetic features.Extreme Gradient Boosting(XGBoost)was used to predict the risk of developing sepsis within 24 h after ED admission.Additionally,SHapley Additive exPlanations(SHAP)was employed to provide a comprehensive interpretation of the model's results.Ten percent of the patients were randomly selected as the testing set,while the remaining patients were used for training with 10-fold cross-validation. RESULTS:For 10-fold cross-validation on 14,957 samples,we reached an accuracy of 84.1%±0.3%and an area under the receiver operating characteristic(ROC)curve of 0.92±0.02.The model achieved similar performance on the testing set of 1,662 patients.SHAP values showed that the five most important features were acuity,arrival transportation,age,shock index,and respiratory rate. CONCLUSION:Machine learning models such as XGBoost may be used for sepsis prediction using only a small amount of data conveniently collected in the ED triage stage.This may help reduce workload in the ED and warn medical workers against the risk of sepsis in advance.

Objective:To analyze the epidemiological features of respiratory syncytial virus (RSV) infection in Beijing, and monitor the sequence variations in RSV glycoprotein (G) gene and clinical features of infected children.Methods:Respiratory tract specimens were collected from children with acute respiratory infection in the Children′s Hospital Affiliated to Capital Institute of Pediatrics from January 1, 2023 to December 31, 2023. RSV-positive specimens screened by multiple nucleic acid testing were subjected to PCR to amplify the full-length RSV G gene. A phylogenetic tree was constructed after gene sequencing to analyze RSV subtypes and trace G gene variants. Clinical data were retrieved from the medical record system to analyze the clinical features of children with RSV infection in Beijing.Results:A total of 5 489 respiratory specimens were collected from 3 046 male patients and 2 443 female patients. The average age of the patients was 4.36 years. A total of 589 RSV-positive specimens (10.7%, 589/5 489) were detected with 349 from male patients and 240 from female patients. The average age of children with RSV infection was (2.51±2.78) years and the median age was 0.48 years. RSV had been circulating among children in Beijing since March 2023 with two epidemic peaks in May (24.6%, 122/496) and December (18.2%, 126/693). The predominant subtype of RSV in the first half of 2023 was subtype A, but it was replaced by subtype B from November 2023. Phylogenetic analysis revealed a novel G gene of RSV subtype B (RSV-B-BA9-954bp) with a length of 954 bp, which belonged to a new cluster in the phylogenetic tree. The percentage of patients admitted to the Intensive Care Unit (ICU) was higher in children with new variant of RSV subtype B infection than in those with common RSV subtype B infection [44.1% (15/34) vs 25.2% (31/123), χ 2=4.600, P=0.032], while the counts of white blood cells and the levels of C-reactive protein were lower in the children with new variant infection ( P<0.05). Conclusions:RSV has been prevalent among children in Beijing since March 2023 with two epidemic peaks. The predominant A subtype is gradually replaced by to B subtype. A new variant of RSV B G gene (RSV-B-BA9-954bp) is detected among the children.