1.Influencing factors of bladder management practices in patients with spinal cord injury
Zhirong LUO ; Xuyan GUO ; Qi XUE ; Xiao TAN ; Yunhua JI ; Fuxun ZHANG ; Yong JIAO ; Bo ZHANG
Journal of Modern Urology 2025;30(4):284-289
Objective: To explore the key factors affecting the selection and effectiveness of bladder management modalities in patients with spinal cord injury,so as to provide reference for the optimization of individualized bladder management strategies. Methods: The clinical and follow-up data of 78 patients with spinal cord injury treated in our hospital during Jan.1,2013 and Dec.31,2022 were retrospectively analyzed.The distribution of bladder management modalities among different grades of injuries was analyzed. Bowker symmetry test was used to evaluate the difference between bladder management modalities at discharge and at the end of follow-up. Multiple linear regression was used to explore the influencing factors of bladder management effects. Plotting Kaplan-Meier survival curves were adopted to calculate the median time of changes in bladder management. Results: At discharge,there were 9 cases of self-catheterization,19 cases of intermittent catheterization,22 cases of reflexive voiding,26 cases of long-term catheterization,and 2 cases using urinary collector.At the end of follow-up,there were 15 cases of self-catheterization,8 cases of intermittent catheterization,34 cases of reflexive voiding,14 cases of long-term catheterization,and 7 cases using urinary collector.There was a significant difference between the modalities of bladder management at discharge and at the end of follow-up (χ
=21.43,P=0.018).Multiple linear regression showed a significant decrease of 8.60 in the total neurogenic bladder symptom score (NBSS) for grade D injuries compared with grade A injuries (P=0.026). The median time to bladder management change was 7.93 months (95%CI:5.44-9.44), with approximately 50% of patients experiencing a change in bladder management within 8 months after discharge. Conclusion: The modalities of bladder management changed significantly after discharge.The grade of injury was a key factor affecting the effectiveness of bladder management.Higher grade was associated with worse effectiveness of bladder management.
2.Analysis of the causal relationship between gut microbiota and bladder cancer with Mendelian randomization
Xuyan GUO ; Zhirong LUO ; Qi XUE ; Yunhua JI ; Xiao TAN ; Yong JIAO
Journal of Modern Urology 2025;30(5):400-407
Objective: Previous observational studies have confirmed the correlation between gut microbiota and bladder cancer,but the causal relationship is still unclear.This study aimed to explore the causal relationship between them with Mendelian randomization. Methods: Genetic variation summary data of 211 gut microbiota and bladder cancer genome-wide association studies (GWAS) were obtained from the MiBioGen Consortium and Finngen database.Single nucleotide polymorphisms (SNPs) closely related to these studies were screened as instrumental variables.The causal relationship between gut microbiota and bladder cancer were analyzed with inverse variance weighting (IVW),MR-Egger,weighted median,maximum likelihood,robust adjustment feature score and MR-PRESSO,with IVW as the primary analysis method.Additionally,sensitivity analysis was used to test the heterogeneity (Cochran Q) and horizontal pleiotropy (MR-Egger intercept term and global test from MR-PRESSO estimator) to ensure the robustness of the results. Results: The IVW results indicated that Lachnospiraceae UCG004 (OR:1.42),Desulfovibrionales (Order) (OR:1.48),Eubacterium ruminantium group (OR:1.33),Olsenella (OR:1.24),Ruminococcaceae UCG002 (OR:1.39),Ruminococcaceae UCG005 (OR:1.42) and Ruminococcaceae UCG013 (OR:1.64) significantly increased the risk of bladder cancer.Conversely,Bacteroidetes (Phylum) (OR:0.61),Eubacterium brachy group (OR:0.80),Ruminococcaceae UCG004 (OR:0.73),Rikenellaceae (Family) (OR:0.67),Lachnospiraceae ND3007 group (OR:0.47), Adlercreutzia (OR:0.73) and an unknow genus (OR:0.75) were associated with a reduced risk of bladder cancer.Sensitivity analyses did not reveal any heterogeneity or horizontal pleiotropy. Conclusion: This study reveals the causal role of 14 gut microbiota in the pathogenesis of bladder cancer,among which Lachnospiraceae UCG004,Desulfovibrionales (Order),Eubacterium ruminantium group,Olsenella,Ruminococcaceae UCG002,Ruminococcaceae UCG005 and Ruminococcaceae UCG013 are risk factors for bladder cancer,while Bacteroidetes (Phylum),Eubacterium brachy group,Ruminococcaceae UCG004,Rikenellaceae (Family),Lachnospiraceae ND3007 group,Adlercreutzia and an unknown genus are the protective factors.
3.Thoughts and practices on research and development of new traditional Chinese medicine drugs under "three combined" evaluation evidence system.
Yu-Qiao LU ; Yao LU ; Geng LI ; Tang-You MAO ; Ji-Hua GUO ; Yong ZHU ; Xue WANG ; Xiao-Xiao ZHANG
China Journal of Chinese Materia Medica 2025;50(7):1994-2000
In recent years, the reform of the registration, evaluation, and approval system for traditional Chinese medicine(TCM) has been promoted at the national level, with establishment of an evaluation evidence system for TCM registration that combines TCM theory, human use experience, and clinical trials(known as the "three-combined" evaluation evidence system). This system, which aligns with the characteristics of TCM clinical practice and the laws of TCM research and development, recognizes the unique value of human use experience in medicine and returns to the essence of medicine as an applied science, thus receiving widespread recognition from both academia and industry. However, it meanwhile poses new and higher challenges. This article delves into the value and challenges faced by the "three-combined" evaluation evidence system from three perspectives: registration management, medical institutions, and the TCM industry. Furthermore, it discusses how the China Association of Chinese Medicine, leveraging its academic platform advantages and leading roles, has made exploratory and practical efforts to facilitate the research and development of new TCM drugs and the implementation of the "three-combined" evaluation evidence system.
Drugs, Chinese Herbal/standards*
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Humans
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Medicine, Chinese Traditional/standards*
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China
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Drug Development
4.Diagnostic value of ultrasonic shear wave elastography for clinically significant prostate cancer.
Fang-Rui YANG ; Yong-Hao JI ; Li-Tao RUAN ; Jian-Xue LIU ; Yao-Ren ZHANG ; Xiao ZHANG ; Qin-Yun WAN ; Si-Fan REN
National Journal of Andrology 2025;31(6):505-511
OBJECTIVE:
To explore the diagnostic value of shear wave elastography (SWE) for clinically significant prostate cancer (csPCa).
METHODS:
We retrospectively analyzed the clinical data of 359 cases with suspected prostate cancer (PCa) in Baoji Central Hospital from June 2017 to July 2023. All the patients underwent the following examinations in the order of serum prostate-specific antigen (PSA) testing, transrectal ultrasonography (TRUS), measurement of the stiffness of the entire prostate gland by SWE, and TRUS-guided prostate puncture biopsy. The stiffness of the entire prostate gland was defined as the average of Young's modulus at both sides of the base, middle, and apex of the prostate, including the maximum Young's modulus (Emax), mean Young's modulus (Emean), and minimum Young's modulus (Emin). We analyzed the correlation of the parameters of the stiffness of the entire prostate gland with the pathological results, focusing on their diagnostic performance for csPCa.
RESULTS:
Of the 359 cases, 189 were diagnosed by pathological puncture biopsy as BPH, 26 as non-csPCa, and 144 as csPCa. The PSA level, Emax, Emean and Emin were significantly higher in the csPCa than those in the BPH and non-csPCa groups (all P < 0.01), but showed no statistically significant difference between the BPH and non-csPCa groups (all P > 0.05). The area under the receiver operating characteristic curve (AUC), optimal cut-off value, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of Emax in the diagnosis of csPCa were 0.852, 143.92 kPa, 72.22%, 84.65%, 75.91%, 81.98% and 79.67%; those of Emean were 0.868, 82.42 kPa, 67.36%, 91.16%, 83.62%, 80.66% and 81.62%; and those of Emin were 0.682, 32.73 kPa, 47.22%, 89.30%, 73.91%, 71.54% and 72.14%, respectively. In the non-csPCa group, Emax, Emean and Emin were found below the optimal cut-off value in 73.08% (19/26), 92.31% (24/26) and 88.46% (23/26), respectively.
CONCLUSION
The stiffness of the entire prostate gland measured by SWE contributes to the diagnosis of csPCa, reduces unnecessary detection of non-csPCa, and provides some reference for its active surveillance.
Humans
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Male
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Prostatic Neoplasms/diagnosis*
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Elasticity Imaging Techniques
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Retrospective Studies
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Prostate/pathology*
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Prostate-Specific Antigen/blood*
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Aged
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Middle Aged
5.Association between Fish Consumption and Stroke Incidence Across Different Predicted Risk Populations: A Prospective Cohort Study from China.
Hong Yue HU ; Fang Chao LIU ; Ke Yong HUANG ; Chong SHEN ; Jian LIAO ; Jian Xin LI ; Chen Xi YUAN ; Ying LI ; Xue Li YANG ; Ji Chun CHEN ; Jie CAO ; Shu Feng CHEN ; Dong Sheng HU ; Jian Feng HUANG ; Xiang Feng LU ; Dong Feng GU
Biomedical and Environmental Sciences 2025;38(1):15-26
OBJECTIVE:
The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks.
METHODS:
A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI).
RESULTS:
During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43).
CONCLUSION
Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans
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China/epidemiology*
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Male
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Female
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Stroke/etiology*
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Middle Aged
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Prospective Studies
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Incidence
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Aged
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Animals
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Fishes
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Risk Factors
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Diet
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Seafood
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Adult
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Cohort Studies
6.Intelligent pre-analytical process reengineering and effect evaluation
Hao XUE ; Yong XIA ; Houlong LUO ; Mingyang LI ; Yaoming YAN ; Ling JI
Chinese Journal of Laboratory Medicine 2024;47(5):520-525
Objective:To improve work efficiency and reduce errors through intelligent pre-analytical process reengineering.Methods:Tumor and infection marker test samples from outpatients at Peking University Shenzhen Hospital from December 2021 to February 2023 were collected. The process was integrated with sample transportation, sample sorting and secondary transfer, and laboratory automation systems, while achieving full-process information monitoring. The number of manual intervention nodes, the turnaround time (TAT) from sample collection to testing and from collection to reporting, the proportion of intelligent pre-dilution, and the number of pre-analytical errors automatically identified were compared before and after the intelligent pre-analytical process reengineering to evaluate the effect of the reengineering. Chi-square test, Fisher′s exact probability method, and Mann-Whitney U test were used for statistical analysis.Results:After implementing the intelligent process reengineering, the number of manual intervention nodes has been reduced from 13 to 2. For outpatient tumor marker samples, after the first stage of reengineering, the median TAT from collection to reporting decreased from 185 (141, 242) min to 137 (102, 183) min ( Z=-54.932, P<0.001). After the second stage of reengineering, the median TAT from collection to reporting further decreased from 137 (102, 183) min to 100 (64, 150) min ( Z=-61.346, P<0.001). For infection marker samples, after the first stage of reengineering, the median TAT from collection to reporting decreased from 392 (282, 1386) min to 229 (176, 323) min ( Z=-68.636, P<0.001). After the second stage of reengineering, the median TAT from collection to reporting further decreased from 229 (176, 323) min to 160 (110, 236) min ( Z=-62.15, P<0.001). Conclusion:Intelligent pre-analytical process reengineering can optimize workflows, improve efficiency, and reduce errors.
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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