1.Cost-utility analysis of semaglutide versus canagliflozin in patients with type 2 diabetes poorly controlled with metformin
Yueru XU ; Yubo WANG ; Huimin PAN ; Huiting SHAN ; Ji CHEN ; Jianhua YANG
China Pharmacy 2025;36(9):1087-1092
OBJECTIVE To evaluate the long-term cost-effectiveness of canagliflozin or semaglutide in patients with type 2 diabetes mellitus(T2DM)poorly controlled with metformin. METHODS Based on the perspective of China’s health system, a Markov model was used to calculate the long-term costs and utilities of canagliflozin or semaglutide combined with metformin for T2DM patients in China for 30 years based on the data from SUSTAIN 8 study. The incremental cost-effectiveness ratio(ICER) and incremental net monetary benefit (INMB) were calculated using one time the 2024 per capita gross domestic product(GDP) as the willingness-to-pay(WTP) threshold. One-way sensitivity analysis, probability sensitivity analysis and scenario analysis were conducted to confirm the stability of the conclusions. RESULTS Compared with canagliflozin + metformin, ICER of semaglutide combined with metformin was 260 485.67 yuan/quality-adjusted life year (QALY),which was higher than the WTP threshold set in this study (95 749 yuan/QALY),and the corresponding INMB was -61 576.24 yuan,indicating that the canagliflozin + metformin regimen was more cost-effective. The cost of diabetes without complications treatment in the semaglutide + metformin group had the greatest influence on INMB,but changes in parameters within the selected range did not drive decision reversal. With the increasing of WTP threshold,the economic acceptability of semaglutide + metformin regimen increased. Under the current WTP threshold,the annual cost of semaglutide should be reduced by 42.95% to make the semaglutide + metformin regimen more cost- effective. CONCLUSIONS From the perspective of China’s health system, canagliflozin + metformin is more cost-effective than semaglutide + metformin for T2DM patients yueru. with poor glycemic control with metformin alone.
2.Brief analysis of the concept of " relaxation and tranquility" and the protection of elderly brain health
Eryu WANG ; Yongyan WANG ; Chenyang QUAN ; Jiawei LIU ; Qiwu XU ; Beibei SHAN ; Yingzhen XIE
Journal of Beijing University of Traditional Chinese Medicine 2025;48(2):291-296
China is currently in an accelerated stage of population aging, and brain diseases pose a significant threat to the health of the elderly. " Preventing brain aging and maintaining brain health" has become a high-level goal of healthy aging. During the process of aging, the physiological and psychological states of elderly people change, making them prone to nervousness and exhaustion, which can disturb the brain spirit, damage the brain collaterals, and severely endanger brain health. Starting from the holistic view of cultivating both body and spirit in traditional Chinese medicine, based on the physical and mental characteristics of the elderly, this paper applies the concept and method of " relaxation and tranquility" in the protection of elderly brain health, focusing on maintaining relaxation and tranquility in both physical and mental aspects. Specific measures include emphasizing subjective consciousness, relaxing the heart and calming down; utilizing the daoyin method, relaxing the body and calming down, combining relaxation and tranquility, cultivating both body and spirit to prevent diseases and protect the brain, which enables the elderly to have a healthy mind and body, a sense of happiness and fulfillment, and to age gracefully. Simultaneously, advocating for tranquility is also called " respect" for relaxation, following nature to understand constant changes, and improving one′s ability to think positively in old age, in order to expand ideas for the protection of elderly brain health.
3.Spatial Distribution Patterns and Environmental Influencing Factors of Flavonoid Glycosides in Epimedium sagittatum
Mengxue LI ; Wenmin ZENG ; Yiting WEI ; Fengqin LI ; Shengfu HU ; Xinyi WANG ; Zhangjian SHAN ; Yanqin XU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(15):217-226
ObjectiveTo explore the spatial distribution patterns of flavonoid glycosides in Epimedium sagittatum and the influences of environmental factors on the accumulation of these components. MethodsThe spatial statistical analysis and GeoDetector model were used to analyze the distribution patterns of epimedin A,epimedin B,epimedin C,icariin,and total flavonoid glycosides in E. sagittatum samples from 92 different production areas in 36 cities of 13 provinces/municipalities/autonomous regions of China,as well as the effects of 28 environmental factors on the accumulation of each component. ResultsThe average content of flavonoid glycosides 64 (69.56%) producing areas and 30 (83.33%) cities met the quality standard of no less than 1.50% of total flavonoid glycosides in the 2020 edition of Chinese Pharmacopoeia.Epimedin A,epimedin B,epimedin C,icariin,and their sum showed significantly high accumulation.The hot spots regions of epimedin A and epimedin B were similar with each other,mainly located in western Hunan,eastern Hubei,eastern Guizhou,and northern Guangxi.The common hot spot areas of epimedin C and total flavonoid glycosides were in western and southwestern Hunan,southern Henan,northern Anhui,eastern Guizhou,and southern Chongqing.The hot spots areas of icariin were in southern Chongqing,western Hunan,and eastern and northeastern Guizhou.The interactions between environmental factors had stronger explanatory power for the accumulation of components than single factors.The strongest single factor and interactive factor affecting the accumulation of epimedin C were precipitation of wettest quarter (q=0.16) and its interaction with temperature seasonality (q=0.35),respectively.The strongest single factor influencing both the accumulation of icariin and total flavonoid glycosides was the precipitation of coldest quarter (q equals 0.15 and 0.22,respectively).The strongest interactions were observed between precipitation of coldest quarter and gravel content (q=0.34),as well as between precipitation of coldest quarter and aspect (q=0.35). ConclusionThirteen cities,including Zhumadian and Nanyang in Henan,Huaihua,Shaoyang,and Zhangjiajie in Hunan,and Zunyi,Qiandongnan,and Tongren in Guizhou,were hot spots of total flavonoid glycosides in E.sagittatum.Precipitation,gravel content,temperature seasonality,and aspect significantly influence the accumulation of flavonoid glycosides in E.sagittatum.This study provides reference for the utilization and production zoning of E.sagittatum.
4.Relationship between traditional Chinese postpartum practices and postpartum depression
Shan CAO ; Jiajun XU ; Yukun KANG ; Peng WANG ; Min JIN
Sichuan Mental Health 2025;38(4):321-326
BackgroundPostpartum depression can affect the physical and mental health of mothers and the quality of parenting. Most Chinese women perform traditional postpartum practices (commonly known as "doing the month") after giving birth, while the existing findings are inconsistent and inconclusive regarding the potential of traditional Chinese postpartum practices to alleviate or exacerbate postpartum depression. ObjectiveTo explore the relationship between traditional Chinese postpartum practices and postpartum depression, so as to provide references for reducing the risk of postpartum depression. MethodsA total of 240 consecutive women who gave birth in the obstetrics department of the Mianyang Central Hospital and the Third Hospital of Mianyang from January to May 2024 were selected. Data were collected using Self-designed General Information Questionnaire, Chinese version of the Edinburgh Postnatal Depression Scale (EPDS), the Social Support Rating Scale (SSRS), the Patient Health Questionnaire-15 (PHQ-15), the Adherence to Doing-the-Month Practices questionnaire (ADP), and the Self-compiled Questionnaire on the Cognition of Doing-the-Month. The absolute value (A value) of the difference between scores of ADP and Cognition of Doing-the-Month Questionnaire was calculated to evaluate the degree of cognitive behavioral conflict of postpartum women. Pearson correlation analysis was performed to examine the correlations of EPDS score with SSRS score, PHQ-15 score, ADP total and dimensional scores, Cognition of Doing-the-Month Questionnaire total and dimensional scores, and A value. Logistic regression analysis was conducted to identify the protective and risk factors for developing postpartum depression. ResultsThe postpartum depression was detected in 22.50% of women. The postpartum women had a EPDS score of (6.21±5.00), ADP score of (70.05±20.57), SSRS score of (41.96±6.96), PHQ-15 score of (4.63±3.77), and Cognition of Doing-the-Month questionnaire score of (40.30±10.13). The A value was (0.65±0.58). Correlation analysis revealed that EPDS score was negatively correlated with the total ADP score and the four dimensional scores of the restrictions on social activities, diet, housework, and personal hygiene (r=-0.228, -0.146, -0.184, -0.275, -0.168, P<0.05 or 0.01), and positively correlated with the A value (r=0.161, P<0.05). Logistic regression analysis indicated that restriction on housework dimension in ADP was entered into the model (OR=0.930, 95% CI: 0.885~0.978). ConclusionThe restriction on housework dimension in traditional Chinese postpartum practices may be a protective factor against postpartum depression.
5.Estimation model for exposure of intravenous busulfan in patients receiving autologous hematopoietic stem cell transplantation
Jin-Wen LI ; Yan XU ; Xiao-Dan WANG ; Ying-Xi LIAO ; Shuai HE ; Shan XU ; Ping ZHANG ; Wen-Juan MIAO
Chinese Pharmacological Bulletin 2024;40(6):1193-1198
Aim To establish limited sampling strategy to esti-mate area under the drug concentration versus time curve(AUC0-t)of lymphoma patients treated with autologous stem cell transplantation(ASCT)who had busulfan intravenous infu-sion.Methods Twelve lymphoma patients treated with ASCT received a conditioning regimen containing busulfan 105 mg·m-2,Ⅳ infusion for 3 h.Blood samples were obtained 1 h after the start of the first dose of the busulfan infusion,at 5 min,1 h,2 h,4 h,6 h and 18 h after the end of the drug administration.LC-MS/MS was used to determine the busulfan serum concentra-tion.After obtaining the clinical pharmacokinetic parameters of busulfan by traditional pharmacokinetic method,multiple linear stepwise regression analysis was used to establish the AUC0-t es-timation model of busulfan based on limited sampling method.The model was further verified by Jackknife and Bootstrap meth-od.Bland-Altman plots were used to evaluate the consistency between the limited sampling method and the classical pharma-cokinetic method.Results The multiple linear regression equa-tion analysis of C60min,C180min and C300min was obtained by the limited sampling method.The regression equation was AUC0-t=295.003C60min+233.050C180min+273.163C300min-1202.713,r2=0.995,MPE=-0.87%,RMSE=2.40%.Conclusion The limited sampling model with three-point estimation can be used to estimate the AUC0-t of busulfan exposure in lymphoma patients with ASCT to provide reference for clinical application of busulfan.
6.Overview of lipid metabolism in pulmonary fibrosis
Jing-Ying WANG ; Yong XU ; Wei-Chen XU ; Tong XIE ; Chen SHI ; Jin-Jun SHAN
Chinese Pharmacological Bulletin 2024;40(9):1612-1616
Pulmonary fibrosis is a diffuse interstitial lung disease with poor prognosis,and its pathogenesis has not been fully clar-ified.Lipid,as a key component of cell structure involved in signal transduction,plays an important role in maintaining lung function.More and more studies show that lipid changes are closely related to the progress of pulmonary fibrosis.This paper briefly reviews the pulmonary fibrosis disease,the research pro-gress of lipidomics in pulmonary fibrosis and the role of various lipids in pulmonary fibrosis.
7.Investigating the cytological mechanisms of paclitaxel-recombinant hirudin interventional coating to prevent restenosis via NF-κB and Notch-1 pathways
Ting WANG ; Yuan-Shan XU ; Hong-Mei LI
Chinese Journal of Interventional Cardiology 2024;32(10):576-587
Objective Investigating how the intervention coating composite of paclitaxel-recombinant hirudin(LFN)regulates the connection between Notch-1 and NF-κB pathways to avoid restenosis.Methods Targets and enrichment analysis of LFN anti-ISR were determined using a network-based technique.Human coronary artery smooth muscle cells(HCASMCs)were employed as a model.Lipopolysaccharide(LPS)and Jagged-1 were utilized to activate the Notch-1 and NF-κB pathways in HCASMCs.It is possible to provide light on the relationship between pathway interactions and the growth and migration of HCASMCs by regulating dual pathways.The mechanism of LFN in preventing and curing postoperative restenosis was explained molecularly.Results Computational results revealed that LFN therapy of in-stent restenosis regulated many biological modules.The ideal modeling setting for inflammatory activation of HCASMCs was found to be 1 μg/ml of LPS and Jagged-1 for 24 hours.When compared to the model group,the migration and proliferation changes of modeling-activated HCASMCs were significantly inhibited by LFN(1 μmol/L paclitaxel with 0.2 mg/ml bivalirudin)at the optimal concentration.This resulted in a down-regulation of NF-κB and Notch-1,an up-regulation of IκBα,and a decrease in the expression of NICD,VEGF,MMP2,MMP9,and Bcl-xL.It also down-regulated the expression of OPN,PCNA,Notch-1,and NF-κB(nucleus)and up-regulated the expression of NF-κ B(cytoplasm)(P<0.05).Among them,the impact of LFN may be directly impacted by changes in Notch-1 and NICD expression.Conclusions LFN prevents restenosis by modulating the Notch-1 and NF-κB pathways and inhibiting the shift of HCASMCs from contractile to synthetic phenotype.
8.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.
9.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.
10.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.


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