OBJECTIVE To evaluate the efficacy and safety of high-dose ilaprazole combined with amoxicillin for newly diagnosed elderly patients with Helicobacter pylori （Hp） infection， and analyze independent risk factors for failure of Hp infection eradication treatment. METHODS Totally 200 cases of newly diagnosed elderly patients with Hp infection in Xinxiang Central Hospital from August 1， 2021 to December 1， 2024 were selected and randomly divided into control group and study group， with 100 cases in each group. The control group was treated with classic quadruple therapy regimen （Amoxicillin capsules+ Clarithromycin tablets+Bismuth potassium citrate tablets+Ilaprazole enteric-coated tablets）. The study group was treated with high- dose Ilaprazole enteric-coated tablets+Amoxicillin capsules. All patients were administered medication for 2 weeks. Hp eradication rates in the two groups were compared using intention-to-treat （ITT） and per-protocol （PP） analyses. The incidence of adverse reactions in both groups was also recorded. The multiple-factor Logistic regression analysis was used to identify independent risk factors for failure of Hp infection eradication treatment. RESULTS In ITT and PP analyses， there was no significant difference of Hp eradication rates between the two groups （P＞0.05）. There was no significant difference in incidence of mild to moderate adverse reactions between the two groups （P＞0.05）. BMI ≤18.5 kg/m2， BMI ＞23.9 kg/m2， rural residence， concomitant diabetes and concomitant heart disease were identified as independent risk factors influencing the failure of Hp infection eradication treatment （P＜0.05）. CONCLUSIONS The efficacy and safety of high-dose ilaprazole combined with amoxicillin are comparable to classic quadruple therapy regimen in treating newly diagnosed elderly patients with Hp infection. Independent risk factors influencing the failure of Hp infection eradication treatment include BMI ≤18.5 kg/m2， BMI ＞23.9 kg/m2， rural residence， concomitant diabetes and concomitant heart disease.

Objective:To apply quality function deployment(QFD)method to formulate management strategy for usage quality of medical equipment,so as to provide a reference for ensuring the safety of using medical equipment.Methods:A questionnaire about the guarantee for the requirement of usage quality of medical equipment was designed,so as to obtain the information of the users of clinical department of The Affiliated Xinghua Hospital to Kangda College of Nanjing Medical University for the requirement of usage quality of medical equipment in using medical equipment from February to April 2024,and confirm the important degree of the requirement.Then,the QFD method was adopted to convert the requirements of users for medical equipment to the required technical indicators of guaranteeing usage quality of medical equipment,and the priority technical guarantee measures of the important degree were quantitatively obtained.Results:A total of 478 questionnaires were issued,and 442 valid questionnaires were retrieved,and the valid recovery rate of questionnaire was 92.47%.The questionnaire identified and analyzed 12 requirements of three dimensions of users in using medical equipment,and they were converted to the top six technical guarantee measures of the strategy of quality management of using medical equipment,which included equipment function,criticality of equipment mission,type of service provider,compliance of rules and regulations,requirements of maintenance,and service life.Conclusion:QFD method can help medical engineering department to establish a management system of usage quality with quantitative analysis for medical equipment,and enhance the management level for the quality of medical equipment in medical institutions,and realize maximize benefit of medical equipment.

Objective The aim of this study is to systematically analyze the therapeutic mechanisms of Wuzi Yuye Decoction in diabetic oligoasthenozoospermia based on network pharmacology and animal experiments.Methods Active components and therapeutic targets of Wuzi Yuye Decoction were screened by integrating multiple databases,and their inter-section with diabetic oligoasthenozoospermia-related targets was obtained.Common targets were identified using the Venny platform,and protein-protein interaction(PPI)networks were constructed via the STRING database.And key targets were screened through topological analysis with Cytoscape.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analyses were performed using the DAVID platform.A mouse model of diabetic oligoasthenozoospermia was established by high-fat diet combined with streptozotocin induction,followed by intervention with Wuzi Yuye Decoction.Body weight,testicular index,and sperm quality were assessed,while histopathological changes were evaluated by HE staining and transmission electron microscopy(TEM).In addition,ELISA,oxidative stress assays and Western blot were used to verify the changes in key pathway-related proteins.Results A total of 36 common targets were identified,including key nodes such as TNF,IL6 and IL1B.Enrichment analysis indicated that these targets were sig-nificantly involved in inflammatory responses,oxidative stress,autophagy-apoptosis regulation and reproduction-related pathways.Animal experiments confirmed that Wuzi Yuye Decoction markedly improved testicular mass and sperm motility in diabetic mice,reduced the levels of AGE,TNF-α,IL-6 and IL-1β in testicular tissues,alleviated oxidative stress damage,and restored autophagic flux and blood-testis barrier function by inhibiting the RAGE/NF-κB/mTOR signaling axis.Conclusion Wuzi Yuye Decoction improves the pathological progression of diabetic oligoasthenozoospermia by synergistically modulating multiple targets,including inflammation inhibition,antioxidant effects,autophagy regulation,and related pathways.

Objective The aim of this study is to systematically analyze the therapeutic mechanisms of Wuzi Yuye Decoction in diabetic oligoasthenozoospermia based on network pharmacology and animal experiments.Methods Active components and therapeutic targets of Wuzi Yuye Decoction were screened by integrating multiple databases,and their inter-section with diabetic oligoasthenozoospermia-related targets was obtained.Common targets were identified using the Venny platform,and protein-protein interaction(PPI)networks were constructed via the STRING database.And key targets were screened through topological analysis with Cytoscape.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analyses were performed using the DAVID platform.A mouse model of diabetic oligoasthenozoospermia was established by high-fat diet combined with streptozotocin induction,followed by intervention with Wuzi Yuye Decoction.Body weight,testicular index,and sperm quality were assessed,while histopathological changes were evaluated by HE staining and transmission electron microscopy(TEM).In addition,ELISA,oxidative stress assays and Western blot were used to verify the changes in key pathway-related proteins.Results A total of 36 common targets were identified,including key nodes such as TNF,IL6 and IL1B.Enrichment analysis indicated that these targets were sig-nificantly involved in inflammatory responses,oxidative stress,autophagy-apoptosis regulation and reproduction-related pathways.Animal experiments confirmed that Wuzi Yuye Decoction markedly improved testicular mass and sperm motility in diabetic mice,reduced the levels of AGE,TNF-α,IL-6 and IL-1β in testicular tissues,alleviated oxidative stress damage,and restored autophagic flux and blood-testis barrier function by inhibiting the RAGE/NF-κB/mTOR signaling axis.Conclusion Wuzi Yuye Decoction improves the pathological progression of diabetic oligoasthenozoospermia by synergistically modulating multiple targets,including inflammation inhibition,antioxidant effects,autophagy regulation,and related pathways.

Objective:To construct a performance evaluation system based on the balanced scorecard (BSC) and key performance indicators (KPI) for medical equipment management in order to effectively measure the management level of medical institutions for medical equipment. Methods:On the basis of literature research and expert consultation,an input,process,output and outcome (IPOO) framework was constructed to describe KPI of medical equipment management based on BSC analysis method. The weights of evaluation indicators were confirmed by factor analysis,and a performance evaluation system for medical equipment management was established. Four medical institutions (hospital 1-4) in Taizhou were selected from June 2023 to October 2023 according to the research items of Kangda College of Nanjing Medical University,and the medical equipment which purchase amount exceeded 500,000 CNY of 4 hospital from 2012 to 2022 were selected. The running data of 2022 was collected,and the management level of 4 hospitals for medical equipment were assessed by this evaluation system. Results:The constructed performance evaluation system about medical equipment management included 4 first-level indicators and 28 second-level indicators. The second-level indicators included 8 input KPI,8 process KPI,6 output KPI,and 6 outcome KPI. The weights of input,process,output and outcome were respectively 0.2853,0.2783,0.2066 and 0.2298. The comprehensive scores of average performance of medical equipment management in hospital 1-4 were respectively 78.88,71.27,66.32 and 70.87 points. The management level of hospital 1 and hospital 2 was better than that of Hospital 3 and Hospital 4. Conclusion:The constructed performance evaluation system of medical equipment management can quantitatively evaluate the management process of medical equipment,and find weak links,and provide continuous improvement,which can provide direction and basis for medical engineering department in improving its performance level.

Objective:To construct a performance evaluation system based on the balanced scorecard (BSC) and key performance indicators (KPI) for medical equipment management in order to effectively measure the management level of medical institutions for medical equipment. Methods:On the basis of literature research and expert consultation,an input,process,output and outcome (IPOO) framework was constructed to describe KPI of medical equipment management based on BSC analysis method. The weights of evaluation indicators were confirmed by factor analysis,and a performance evaluation system for medical equipment management was established. Four medical institutions (hospital 1-4) in Taizhou were selected from June 2023 to October 2023 according to the research items of Kangda College of Nanjing Medical University,and the medical equipment which purchase amount exceeded 500,000 CNY of 4 hospital from 2012 to 2022 were selected. The running data of 2022 was collected,and the management level of 4 hospitals for medical equipment were assessed by this evaluation system. Results:The constructed performance evaluation system about medical equipment management included 4 first-level indicators and 28 second-level indicators. The second-level indicators included 8 input KPI,8 process KPI,6 output KPI,and 6 outcome KPI. The weights of input,process,output and outcome were respectively 0.2853,0.2783,0.2066 and 0.2298. The comprehensive scores of average performance of medical equipment management in hospital 1-4 were respectively 78.88,71.27,66.32 and 70.87 points. The management level of hospital 1 and hospital 2 was better than that of Hospital 3 and Hospital 4. Conclusion:The constructed performance evaluation system of medical equipment management can quantitatively evaluate the management process of medical equipment,and find weak links,and provide continuous improvement,which can provide direction and basis for medical engineering department in improving its performance level.

Objective:To apply quality function deployment(QFD)method to formulate management strategy for usage quality of medical equipment,so as to provide a reference for ensuring the safety of using medical equipment.Methods:A questionnaire about the guarantee for the requirement of usage quality of medical equipment was designed,so as to obtain the information of the users of clinical department of The Affiliated Xinghua Hospital to Kangda College of Nanjing Medical University for the requirement of usage quality of medical equipment in using medical equipment from February to April 2024,and confirm the important degree of the requirement.Then,the QFD method was adopted to convert the requirements of users for medical equipment to the required technical indicators of guaranteeing usage quality of medical equipment,and the priority technical guarantee measures of the important degree were quantitatively obtained.Results:A total of 478 questionnaires were issued,and 442 valid questionnaires were retrieved,and the valid recovery rate of questionnaire was 92.47%.The questionnaire identified and analyzed 12 requirements of three dimensions of users in using medical equipment,and they were converted to the top six technical guarantee measures of the strategy of quality management of using medical equipment,which included equipment function,criticality of equipment mission,type of service provider,compliance of rules and regulations,requirements of maintenance,and service life.Conclusion:QFD method can help medical engineering department to establish a management system of usage quality with quantitative analysis for medical equipment,and enhance the management level for the quality of medical equipment in medical institutions,and realize maximize benefit of medical equipment.

Objective To investigate the influence of serum cystatin C (Cys-C) and hypersensitivity C-reactive protein (hs-CRP) levels on the 3-year survival of patients undergoing maintenance hemodialysis (MHD). Methods A total of 358 patients with chronic renal failure who underwent MHD at the Second Affiliated Hospital of Nantong University from April 2011 to October 2020 were selected as study subjects. General clinical data, pre-dialysis laboratory test indicators, and echocardiographic indicators 3 months after dialysis were recorded. The survival status of patients after 3 years of dialysis was followed up, and the general clinical data, pre-dialysis laboratory test indicators, and echocardiographic indicators 3 months after dialysis were compared between surviving and deceased patients. Univariate and multivariate Cox regression analyses were performed to screen influencing factors of 3-year survival in MHD patients. Results At the 3-year follow-up, of the 302 MHD patients' 203 survived, and 99 died. Statistically significant differences were observed in age, primary disease, diabetes status, congestive heart failure, statin use, antiplatelet drug use, diuretic use, dialysis mode, estimated glomerular filtration rate (eGFR) and gamma-glutamyl transferase (GGT), alkaline phosphatase (AKP), total bilirubin (TBIL), β₂-microglobulin (β₂-MG), creatinine (Cr), low-density lipoprotein cholesterol (LDL-C), hypersensitive C-reactive protein (hs-CRP), and serum phosphorus (P) levels between surviving patients and deaths(P < 0.05 or P < 0.01). Univariate Cox regression results showed that age of MHD patients, primary disease (diabetic nephropathy, hypertensive nephropathy, polycystic kidney disease, others), comorbidities(diabetes, congestive heart failure, other cardiovascular diseases), drug use (statins, antiplatelet drugs), dialysis method (hemodialysis, hemodialysis + perfusion), laboratory test indicators [GGT, AKP, TBIL, total bile acid (TBA), albumin (ALB), Cr, Cys-C, eGFR, apolipoprotein A (APO-A), hs-CRP]were all influential factors of 3-year survival rate of MHD patients. Multivariate Cox regression analysis revealed that age, primary disease, other cardiovascular diseases, dialysis mode, AKP, ALB, TBIL, Cys-C, and hs-CRP were significant influencing factors for the survival of patients with chronic renal failure (P < 0.05). Conclusion Serum Cys-C and hs-CRP levels before MHD in patients with chronic renal failure may be associated with their 3-year survival after dialysis treatment. High serum Cys-C may reduce the risk of poor clinical prognosis, while high serum hs-CRP may increase the risk of poor clinical prognosis.

Objective:To identify serum metabolic markers for early prediction and diagnosis of gestational diabetes mellitus (GDM).Methods:A retrospective case-control study was conducted.The study subjects were from pregnant women enrolled in the Birth Cohort Study of the Women′s Hospital, Zhejiang University, from1 November 2018 to 30 March 2020.100 cases of GDM (GDM group, Age 36.03±3.91) and 150 non-GDM pregnant women matched for clinical information (control group, Age35.49±3.46) were retrospectively selected for the study. Fasting serum samples were collected at 15-20 weeks of gestation (prior to GDM diagnosis, T1 period) and 24-28 weeks of gestation (during GDM diagnosis, T2 period). Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to quantify GDM-related serum metabolic small molecules, including 1, 5-anhydroglucitol, 3-hydroxybutyric acid, phenylalanine, and isoleucine. These molecules, along with basic clinical information (age, gestational week, BMI) and standard biochemical indicators (FPG), were used to develop predictive models for the early detection of GDM at T1 and the diagnosis of GDM at T2. Statistical analysis was performed using t-tests or Mann-Whitney U-tests.Result:The results of the targeted quantitative validation study indicate: At the T1 stage, the level of 1, 5-anhydroglucitol was found to be significantly lower ( P=0.001) in the GDM group compared to the control group. Conversely, the level of isoleucine was significantly higher ( P=0.027) in the GDM group. There were no significant differences in the levels of 3-hydroxybutyrate and phenylalanine between the two groups ( P>0.05). The combination of the 4 metabolites yielded the highest predictive value (AUC) for GDM at T1, with an AUC of 0.670 (95% CI: 0.602-0.739), P<0.001.At the T2 stage, the GDM group had significantly lower levels of 1, 5-anhydroglucitol ( P<0.05) and significantly higher levels of 3-hydroxybutyric acid and isoleucine ( P<0.05) than the control group, with no significant differences in phenylalanine levels ( P=0.626). The combination of the four metabolites had the highest diagnostic value (AUC) for GDM, 0.717 (95% CI 0.651-0.783), P<0.001.The analysis of seven different combinations of GDM prediction/diagnostic models created by combining four metabolites with basic clinical information and routine biochemical indicators showed: We found that the AUC value of the GDM diagnostic model built with FPG, BMI, pre-pregnancy BMI, age, gestational week, and the 4 metabolite indicators in T2 stage was the best, 0.794 (95% CI 0.736-0.851), P<0.001, with a sensitivity of 72%;The best AUC value for the GDM prediction model built with the same indicators at T1 was 0.711(95% CI 0.646-0.776), P<0.001, with a sensitivity of 77%. Conclusions:Four metabolic small molecules, 1, 5-anhydroxyglucitol, 3-hydroxybutyric acid, phenylalanine, and isoleucine, were integrated with clinical indicators (FPG) and clinical information (age, gestational week, BMI) to develop a predictive model for GDM at gestation (T1) and a diagnostic model for GDM at gestation (T2), demonstrating promising clinical prediction and diagnostic capabilities. 1, 5-Anhydroglucitol, 3-hydroxybutyric acid, phenylalanine, and isoleucine show potential as valuable markers for the prediction and diagnosis of GDM.

Objective:To explore the factors affecting the management of medical devices in the COVID-19 pandemic, and to provide guidance for the management of medical devices in public health emergencies.Methods:A total of 184 hospitals caring COVID-19 patients in Jiangsu, Zhejiang, Shanghai, Anhui and Shandong were selected, and clinical engineers were randomly sampled. A self-compiled questionnaire was used to conduct an online survey on factors affecting medical device management during the COVID-19 pandemic from August to December 2021.The index system of influencing factors of medical device management during the COVID-19 pandemic was determined through an exploratory factor analysis, and then the structural equation model was used to verify the rationality and scientificity of the index system, while the relative weight method was used to calculate the weight of the index system.Results:277 valid questionnaires were recovered. Through the exploratory factor analysis, an index system of influencing factors of medical device management was established, which consisted of such level-indexes as the human factor, device factor, material factor, method factor, and environment factor, as well as 17 level-2 indexes. The fitness-indexes of the second-order structural equation model were finally fitted as follows: the chi-square to freedom ratio was 2.606, the approximate root mean square error was 0.076, and the value of value-added adaptation index, non-standard adaptation index and comparative adaptation index were 0.921, 0.903 and 0.920, respectively. The weights of the method factor, human factor, device factor, material factor and environment factor of the level-1 indexes were 0.216, 0.191, 0.175, 0.274 and 0.144, respectively. Such factors as manpower, regulations and institutional processes, and information technology ranked top three among the 17 level-2 indexes, which were 0.090, 0.082 and 0.080 respectively.Conclusions:The influencing factor model of medical device management during the COVID-19 pandemic in this study is ideal; human factors and method factors are the influencing factors deserving high priority in medical device management during the COVID-19 pandemic. Ensuring sufficient human resources, improving laws, regulations and processes, as well as enhancing information management level are breakthroughs expected in medical device management.