1.Alteration of cognitive function in overweight and obese adolescents and its relationship with serum FGF21 levels
Rui HAN ; Qian WU ; Dan LIU ; Di CHENG ; Ying ZHANG ; Jiacheng NI ; Piao KANG ; Anran CHEN ; Shujie YU ; Qichen FANG ; Huating LI
Journal of Shanghai Jiaotong University(Medical Science) 2024;44(1):87-97
Objective·To evaluate the changes in cognitive function in overweight and obese adolescents,and explore the association between cognitive function and fibroblast growth factor 21(FGF21).Methods·A total of 175 adolescents from a senior high school in Shanghai were divided into normal weight group(n=50),overweight group(n=50)and obese group(n=75)based on their body mass index(BMI).General information,anthropometric data and laboratory testing indicators of the adolescents were collected and compared.The cognitive function of the three groups of adolescents was assessed by using the accuracy(ACC)and reaction time of Flanker task and n-back task.Enzyme-linked immunosorbent assay(ELISA)was used to detect the serum FGF21 level of the three groups of adolescents.Partial correlation analysis and multiple linear regression model were used to evaluate the correlation between cognitive task performance and anthropometric data and laboratory testing indicators.Results·Compared with the normal weight group,systolic blood pressure,diastolic blood pressure,and the levels of fasting plasma glucose,glycosylated hemoglobin and triacylglycerol in the obese group were higher(all P<0.05).Under congruent or incongruent stimulus conditions in the Flanker task,there was no significant difference in ACC between any two groups;compared with the normal weight and overweight groups,the reaction time of the adolescents in the obese group was prolonged(all P<0.05).In the n-back task,there were no significant differences in ACC between any two groups,while the obese group had longer reaction time in the 1-back and 2-back tasks compared to the normal weight and overweight groups(all P<0.05).Compared with the normal weight group,serum FGF21 levels of the adolescents in the obese group were higher(P=0.000).Partial correlation analysis showed that the reaction time of the adolescents in Flanker and n-back tasks was correlated with their BMI,body fat mass,waist circumference,waist-to-hip ratio and FGF21 level(all P<0.05).Multiple linear regression analysis further confirmed that BMI was associated with prolonged reaction time in cognitive-related behavioral tasks in the adolescents(all P<0.05),and FGF21 level was associated with ACC in the 2-back task(P=0.000)and reaction time in the incongruent stimulus condition(P=0.048).Conclusion·Overweight and obese adolescents have cognitive impairments,and BMI and serum FGF21 levels are associated with changes in their cognitive function.
2.Role of paeoniflorin in the treatment of diabetes based on network pharmacology and molecular docking
Si-Yao SONG ; Peng LU ; Ding-Xiao WU ; Da KANG ; Yu-Hui HE ; Ying LÜ ; Yan LIN
The Chinese Journal of Clinical Pharmacology 2024;40(15):2261-2264
Objective To explore the potential mechanism of action of paeoniflorin in diabetes mellitus,the related targets and pathways were preliminarily discussed,based on the network pharmacology and molecular docking technology.Methods Analyze the potential targets of paeoniflorin using the Swiss Target Prediction database.Genecards and OMIM databases yielded the genes of diabetes-related illnesses.After taking the intersection of the two,protein-protein interaction network(PPI)was established using STRING and Cytoscape programs to search for key genes with strong correlation and complete gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis.Use AutoDockTools and Pymol programs to complete protein molecule docking validation.Results The pharmacologically-related study revealed 63 targets associated with paeoniflorin,4 758 genes related to diabetes,and 50 intersection targets.15 key genes including vascular endothelial growth factor A(VEGFA),epidermal growth factor receptor(EGFR),V-Ha-ras harvey(HRAS),V-src sarcoma(SRC)and heat shock protein hs 90-alpha(HSP90AA1)were screened.RAs-associated protein 1,Ras,calcium and other signaling pathways were obtained by KEGG pathway analysis.Molecular docking results showed that paeoniflorin had good binding ability with key genes.Conclusion Paeoniflorin can treat diabetes through multiple targets and pathways,and this mechanism can provide a basis for the application of paeoniflorin in anti diabetes and drug research and development.
3.Impact of therapeutic plasma exchange intervention timing and liver injury periodization on the prognosis of pa-tients with exertional heat stroke
Zongzhong HE ; Min WANG ; Yuan ZHUANG ; Jie LIN ; Leiying ZHANG ; Liyang ZOU ; Lingling LI ; Chunya MA ; Xiaomin LIU ; Xiang QUAN ; Ying JIANG ; Mou ZHOU ; Hongjun KANG ; Yang YU
Chinese Journal of Blood Transfusion 2024;37(7):728-733
Objective To explore the prognostic impact and clinical application value of therapeutic plasma exchange(TPE)intervention timing and liver injury periodization in patients with exertional heat stroke(EHS).Methods Data of 127 EHS patients from the First Medical Center of the General Hospital of the People′s Liberation Army from January 2011 to December 2023 were collected,then divided into the death group and the survival group based on therapeutic outcomes and into 5 stages according to the dynamic changes of ALT,AST,TBIL and DBIL.According to propensity score matching analysis,11 patients in the survival group and 12 patients in the death group were included in the statistical analysis,and 20 of them were treated with TPE.The changes in indicators and clinical outcomes before and after TPE were observed,in order to evaluate the impact of intervention timing on prognosis.Results Among the 23 patients,14 had no liver injury or could progress to the repair phase,resulting in 3 deaths(with the mortality rate of 21.43%),while 9 patients failed to pro-gress to the repair phase,resulting in 9 deaths(with the mortality rate of 100%),with significant differences(P<0.05).The mortality rate of the first TPE intervention before the third stage of liver injury was 23.08%(3/13),while that of interven-tion after reaching or exceeding the third stage was 85.71%(6/7),and the difference was statistically significant(P<0.05).Conclusion TPE should be executed actively in EHS patients combined with liver injury before the third phase to lock its pathological and physiological processes,thereby improving prognosis and reducing mortality.
4.Establishment and application of measurement range of main blood quality indicators in provincial blood stations
Zixuan ZHANG ; Ying CHANG ; Xiaotong ZHANG ; Qingming WANG ; Yuan ZHANG ; Yue LIU ; Qinghua TIAN ; Ka LI ; Guorong LI ; Lixia CHEN ; Junhua SUN ; Yu KANG ; Pingchen HAN ; Xinyu ZHAO ; Song LI
Chinese Journal of Blood Transfusion 2024;37(8):918-926
Objective To obtain the monitoring measurement range of quality indicators of red blood cells,plasma and derivatives and leukocyte-reduced apheresis platelets provided by blood stations in Hebei province,explore the distribution of monitoring values and the change of monitoring level,so as to further strengthen the homogenization construction of quality control laboratories in blood stations in Hebei.Methods In 2023,the sampling data of 12 blood stations in Hebei from 2015 to 2022 were collected,scatter plots were made and the range markers were set,and the"mean±SD"line was taken as the upper limit and lower limit of the measurement range.In 2024,the monitoring values in 2023 were added,and the changes of two measurement ranges were compared to analyze the stability and overall level.Results Comparison of the measurement range from 2015 to 2022 and the measurement range from 2015 to 2023 showed that the standard deviation of the content of deleukocyte suspension of red blood cells-hemoglobin,washed erythrocyte-hemoglobin,washed erythrocyte-su-pernatant protein,cryoprecipitate coagulation factor-FⅧ,fresh frozen plasma-FⅧ,leukocyte-reduced apheresis platelets-leukocyte residue and leukocyte-reduced apheresis platelet-red blood cell concentration decreased from 8.132 to 7.993,6.252 to 6.104,0.273 to 0.267,57.506 to 56.276,0.920 to 0.892,0.653 to 0.644 and 2.653 to 2.603,respectively.The narrowing of the standard deviation range of the above items led to more concentrated monitoring values and reduced disper-sion.Comparison of the measurement range from 2015 to 2022 and the measurement range from 2015 to 2023 showed that the mean value of leukocyte residue of the deleukocyte suspension of red blood cells,hemoglobin content of the wash eryth-rocyte,protein content of supernatant of the wash erythrocyte,hemolysis rate of the wash erythrocyte,FⅧ content of the cryoprecipitate coagulation factor,plasma protein content of the fresh frozen plasma,FⅧ content of the fresh frozen plasma,platelet content of the leukocyte-reduced apheresis platelets changed from 0.362 to 0.476,44.915 to 44.861,0.280 to 0.283,0.137 to 0.142,133.989 to 133.271,60.262 to 60.208,1.301 to 1.277 and 3.036 to 3.033,respectively,and was closer to the national standard line,which reflects an increase in the number of unqualified monitoring values or values close to the national standard line in 2023.The long-term qualified rate of coagulation items was low,and no improvement has been ob-served.The stability of biochemical items has been enhanced but overall deviation has occurred,with the average value close to the national standard line.The possibility of subsequent testing failure has increased.The counting items showed no obvi-ous common characteristics.Conclusion The use of"mean±SD"in the analysis can visually display the distribution of mo-nitoring values of different items in Hebei,forming an indicator measurement range covering the past nine years.It shows the characteristics of each item,and provides reference for subsequent quality control laboratory data analysis of each blood sta-tions to takes active measures to improve the monitoring level.
5.Construction of the Whole Process Management Model of Hospice and Palliative Care Outpatient Clinic
Yaoxin ZENG ; Xiaohong NING ; Ying ZHENG ; Zhiyuan ZHANG ; Yiyou WANG ; Yu ZHANG ; Qian KANG
Acta Academiae Medicinae Sinicae 2024;46(2):210-216
Objective To construct a scientific and practical management model of the hospice and pal-liative care outpatient clinic and provide a reference for the operation and development of the outpatient clin-ic.Methods The basic framework of the whole process management model of hospice and palliative care outpa-tient clinic was determined preliminarily by literature analysis,qualitative interviews and experts group meet-ings.Two rounds of consultation were conducted among 18 experts in hospice and palliative care and medical-nursing combined outpatient service by the Delphi method.Results The questionnaire response rates of the two rounds of expert consultation were both 100%and the authority coefficients of the two rounds of expert consultation were 0.88 and 0.91,respectively.Finally,the whole process management model of hospice and palliative care out-patient clinic was constructed,which was composed of three first-level indicators including staff composition,work structure and effect evaluation,5 second-level indicators and 62 third-level indicators.Conclusion The construc-ted whole process management model is scientific,innovative and continuous,which can provide a reference for the operation and development of the hospice and palliative care outpatient clinic.
6.Application efficacy of FMEA management model-based risk assessment in prevention and control of healthcare-associated infection:a Meta-analysis
Ling CAI ; Kang-Le GUO ; Yan WANG ; Ying-Hua ZHANG ; Yu-Qing FAN ; Xiao-Hong ZHANG ; Lan-Wen HU ; Ya-Hong YANG ; Hao-Jun ZHANG
Chinese Journal of Infection Control 2024;23(11):1350-1357
Objective To systematically evaluate the application efficacy of failure mode and effect analysis(FMEA)management mode in the prevention and control of healthcare-associated infection(HAI).Methods Li-terature on the application of FMEA management mode in HAI prevention and control were retrieved from PubMed,Embase,the Cochrane Library,China National Knowledge Infrastructure(CNKI),VIP Database,Wanfang Data-base,and China Biomedical Literature Database(CBM).Two researchers independently screened the literature,ex-tracted data,and conducted cross checking.Risk and quality assessments were performed on the included studies of randomized controlled trials by ROB tool,the included cohort studies were scored by Newcastle-Ottawa(NOS)scale,and Meta-analysis was conducted by RevMan 5.4 software.Results A total of 22 studies involving 42 815 patients were included in the analysis,with 21 784 in the FMEA management mode group and 21 031 in the control group.Meta-analysis results showed that the incidence of HAI in the FMEA management mode group was lower than that in the control group(OR=0.31,95%CI[0.24,0.40]).Compared with the conventional management mode,incidences of superficial surgical site infection(OR=0.53,95%CI[0.36,0.78]),respiratory system infec-tion(OR=0.44,95%CI[0.35,0.56]),urinary system infection(OR=0.45,95%CI[0.38,0.53]),and blood system infection(OR=0.29,95%CI[0.18,0.45])in the FMEA management mode group were all lower(all P<0.01).Conclusion The application of FMEA management mode in HAI prevention and control can reduce the inci-dence of HAI,which should be actively promoted in hospital management.
7.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
8.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
9.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
10.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.

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