1.Analysis of impact of host plants on quality of Taxilli Herba based on widely targeted metabolomics.
Dong-Lan ZHOU ; Zi-Shu CHAI ; Mei RU ; Fei-Ying HUANG ; Xie-Jun ZHANG ; Min GUO ; Yong-Hua LI
China Journal of Chinese Materia Medica 2025;50(12):3281-3290
This study aims to explore the impact of host plants on the quality of Taxilli Herba and provide a theoretical basis for the quality control of Taxilli Herba. The components of Taxilli Herba from three different host plants(Morus alba, Salix babylonica, and Cinnamomum cassia) and its 3 hosts(mulberry branch, willow branch, and cinnamon branch) were detected by widely targeted metabolomics based on ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS). Principal component analysis(PCA), orthogonal partial least squares discriminant analysis(OPLS-DA), and Venn diagram were employed for analysis. A total of 717 metabolites were detected in Taxilli Herba from the three host plants and the branches of these host plants by UPLC-MS/MS. The results of PCA and OPLS-DA of Taxilli Herba from the three different host plants showed an obvious separation trend due to the different effects of host plants. The Venn diagram showed that there were 32, 8, and 26 characteristic metabolites in samples of Taxilli Herba from M. alba host, S. babylonica host, and C. cassia host, respectively. It was found by comparing the characteristic metabolites of Taxilli Herba and its hosts that each host transmits its characteristic components to Taxilli Herba, so that the Taxilli Herba contains the characteristic components of the host. The Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis showed that the differential metabolites of Taxilli Herba from the three hosts were mainly enriched in flavonoid biosynthesis, arginine and proline metabolism, and glycolysis/gluconeogenesis pathways. Furthermore, the differential metabolites enriching pathways of Taxilli Herba from the three hosts were different depending on the host. In a word, host plants have a significant impact on the metabolites of Taxilli Herba, and it may be an important factor for the quality of Taxilli Herba.
Metabolomics/methods*
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Drugs, Chinese Herbal/chemistry*
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Chromatography, High Pressure Liquid
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Tandem Mass Spectrometry
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Quality Control
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Salix/chemistry*
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Cinnamomum aromaticum/metabolism*
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Principal Component Analysis
2.Prediction of testicular histology in azoospermia patients through deep learning-enabled two-dimensional grayscale ultrasound.
Jia-Ying HU ; Zhen-Zhe LIN ; Li DING ; Zhi-Xing ZHANG ; Wan-Ling HUANG ; Sha-Sha HUANG ; Bin LI ; Xiao-Yan XIE ; Ming-De LU ; Chun-Hua DENG ; Hao-Tian LIN ; Yong GAO ; Zhu WANG
Asian Journal of Andrology 2025;27(2):254-260
Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans
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Male
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Azoospermia/diagnostic imaging*
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Deep Learning
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Testis/pathology*
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Retrospective Studies
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Adult
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Ultrasonography/methods*
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Sperm Retrieval
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Sertoli Cell-Only Syndrome/diagnostic imaging*
3.International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025).
Sheng-Sheng ZHANG ; Lu-Qing ZHAO ; Xiao-Hua HOU ; Zhao-Xiang BIAN ; Jian-Hua ZHENG ; Hai-He TIAN ; Guan-Hu YANG ; Won-Sook HONG ; Yu-Ying HE ; Li LIU ; Hong SHEN ; Yan-Ping LI ; Sheng XIE ; Jin SHU ; Bin-Fang ZENG ; Jun-Xiang LI ; Zhen LIU ; Zheng-Hua XIAO ; Jing-Dong XIAO ; Pei-Yong ZHENG ; Shao-Gang HUANG ; Sheng-Liang CHEN ; Gui-Jun FEI
Journal of Integrative Medicine 2025;23(5):502-518
Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy*
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Humans
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Medicine, Chinese Traditional/methods*
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Practice Guidelines as Topic
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Drugs, Chinese Herbal/therapeutic use*
4.Experts consensus on standard items of the cohort construction and quality control of temporomandibular joint diseases (2024)
Min HU ; Chi YANG ; Huawei LIU ; Haixia LU ; Chen YAO ; Qiufei XIE ; Yongjin CHEN ; Kaiyuan FU ; Bing FANG ; Songsong ZHU ; Qing ZHOU ; Zhiye CHEN ; Yaomin ZHU ; Qingbin ZHANG ; Ying YAN ; Xing LONG ; Zhiyong LI ; Yehua GAN ; Shibin YU ; Yuxing BAI ; Yi ZHANG ; Yanyi WANG ; Jie LEI ; Yong CHENG ; Changkui LIU ; Ye CAO ; Dongmei HE ; Ning WEN ; Shanyong ZHANG ; Minjie CHEN ; Guoliang JIAO ; Xinhua LIU ; Hua JIANG ; Yang HE ; Pei SHEN ; Haitao HUANG ; Yongfeng LI ; Jisi ZHENG ; Jing GUO ; Lisheng ZHAO ; Laiqing XU
Chinese Journal of Stomatology 2024;59(10):977-987
Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.
5.Expert Consensus on Standard Terminology for Hair Transplantation (2024 Edition)
Yong MIAO ; Wei WU ; Zhenyu GONG ; Wenjie JIANG ; Yufei LI ; Zhiqi HU ; Hua XIAN ; Xiang XIE ; Weiqi YANG ; Dongyi ZHANG ; Jufang ZHANG ; Jiaxian ZHANG ; Chunhua ZHANG
Medical Journal of Peking Union Medical College Hospital 2024;15(6):1301-1310
In order to promote the development of hair transplantation, particularly the establishment of standards, the Hair Transplantation Expert Group of Plastic and Aesthetic National Medical Quality Control Center invited experts in the field of hair transplantation across China and formed a draft of the
6.Longitudinal extrauterine growth restriction in extremely preterm infants: current status and prediction model
Xiaofang HUANG ; Qi FENG ; Shuaijun LI ; Xiuying TIAN ; Yong JI ; Ying ZHOU ; Bo TIAN ; Yuemei LI ; Wei GUO ; Shufen ZHAI ; Haiying HE ; Xia LIU ; Rongxiu ZHENG ; Shasha FAN ; Li MA ; Hongyun WANG ; Xiaoying WANG ; Shanyamei HUANG ; Jinyu LI ; Hua XIE ; Xiaoxiang LI ; Pingping ZHANG ; Hua MEI ; Yanju HU ; Ming YANG ; Lu CHEN ; Yajing LI ; Xiaohong GU ; Shengshun QUE ; Xiaoxian YAN ; Haijuan WANG ; Lixia SUN ; Liang ZHANG ; Jiuye GUO
Chinese Journal of Neonatology 2024;39(3):136-144
Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.
7.Expert Consensus on Standard Terminology for Hair Transplantation (2024 Edition)
Yong MIAO ; Wei WU ; Zhenyu GONG ; Wenjie JIANG ; Yufei LI ; Zhiqi HU ; Hua XIAN ; Xiang XIE ; Weiqi YANG ; Dongyi ZHANG ; Jufang ZHANG ; Jiaxian ZHANG ; Chunhua ZHANG ; HAIR TRANSPLANTATION EXPERT GROUP OF PLASTIC AND AESTHETIC NATIONAL MEDICAL QUALITY CONTROL CENTER
Medical Journal of Peking Union Medical College Hospital 2024;15(6):1301-1310
In order to promote the development of hair transplantation, particularly the establishment of standards, the Hair Transplantation Expert Group of Plastic and Aesthetic National Medical Quality Control Center invited experts in the field of hair transplantation across China and formed a draft of the
8.Factors of prognosis of patients with acute myocardial infarction complicated with cardiogenic shock undergoing primary percutaneous coronary intervention under the support of mechanical devices
Ming-Hua LUO ; Yu-Shan CHEN ; He WANG ; Huai-Min GUAN ; Jin-Hong XIE ; Cheng-Jie QIU ; Yong-Hua ZONG ; Sha-Sha SHANG ; Yun-Wei WANG
Chinese Journal of Interventional Cardiology 2024;32(4):197-202
Objective To investigate the factors influencing prognosis in patients with acute myocardial infarction complicated with cardiogenic shock undergoing primary percutaneous coronary intervention(PPCI).Methods Patients with acute myocardial infarction complicated with cardiogenic shock who underwent PPCI at our hospital between January 2015 and December 2019 were enrolled.Clinical baseline characteristics,coronary angiography and PCI-related parameters,and mechanical support information were collected.The patients were followed up for one year and divided into survival and death groups based on their survival status within one year.Differences in various factors between the two groups were compared.Results A total of 40 patients were enrolled,including 26 in the survival group and 14 in the death group.There were no differences in baseline data,diagnosis,risk factors,and comorbidities between the two groups.The survival group had a lower heart rate and higher blood pressure trend at admission compared to the death group.Myocardial enzymes were significantly lower in the survival group compared to the death group(median CK peak:496.00(198.25,2 830.00)U/L vs.3 040.00(405.75,5 626.53)U/L,P=0.003;median CK-MB peak:52.65(31.75,219.50)U/L vs.306.00(27.25,489.63)U/L,P=0.006).When comparing coronary angiography and PCI-related indicators between the two groups,the survival group had a higher rate of complete revascularization compared to the control group(53.85%vs.21.43%,P=0.048).The survival group had a higher proportion of extracorporeal membrane oxygenation(ECMO)combined with intra-aortic balloon pump(IABP)support compared to the control group[38.46%vs.7.14%,P=0.034].Conclusions Survival in patients with acute myocardial infarction complicated with cardiogenic shock undergoing PPCI is associated with lower level of myocardial enzymes,ECMO combined with IABP support and complete revascularization.
9.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.
10.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.

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