1.Interpretation and thoughts on the formulation and revision of the standards for exogenous harmful residues in traditional Chinese medicinal materials in the Chinese Pharmacopoeia 2025 Edition
WANG Ying ; SHEN Mingrui ; LIU Yuanxi ; ZUO Tiantian ; WANG Dandan ; HE Yi ; CHENG Xianlong ; JIN Hongyu ; LIU Yongli ; WEI Feng ; MA Shuangcheng
Drug Standards of China 2025;26(1):083-092
As people’s attention to health continues to increase, the market demand for traditional Chinese medicine (TCM) is growing steadily. The quality and safety of Chinese medicinal materials have attracted unprecedented social attention. In particular, the issue of exogenous harmful residue pollution in TCM has become a hot topic of concern for both regulatory authorities and society. The Chinese Pharmacopoeia 2025 Edition further refines the detection methods and limit standards for exogenous harmful residues in TCM. This not only reflects China’s high-level emphasis on the quality and safety of TCM but also demonstrates the continuous progress made by China in the field of TCM safety supervision. Basis on this study, by systematically reviewing the development history of the detection standards for exogenous harmful residues in TCM and analyzing the revisions and updates of these detection standards in the Chinese Pharmacopoeia 2025 Edition, deeply explores the key points of the changes in the monitoring standards for exogenous harmful residues in TCM in the Chinese Pharmacopoeia 2025 Edition. Moreover, it interprets the future development directions of the detection of exogenous residues in TCM, aiming to provide a reference for the formulation of TCM safety supervision policies.
2.Criteria and prognostic models for patients with hepatocellular carcinoma undergoing liver transplantation
Meng SHA ; Jun WANG ; Jie CAO ; Zhi-Hui ZOU ; Xiao-ye QU ; Zhi-feng XI ; Chuan SHEN ; Ying TONG ; Jian-jun ZHANG ; Seogsong JEONG ; Qiang XIA
Clinical and Molecular Hepatology 2025;31(Suppl):S285-S300
Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.
3.Criteria and prognostic models for patients with hepatocellular carcinoma undergoing liver transplantation
Meng SHA ; Jun WANG ; Jie CAO ; Zhi-Hui ZOU ; Xiao-ye QU ; Zhi-feng XI ; Chuan SHEN ; Ying TONG ; Jian-jun ZHANG ; Seogsong JEONG ; Qiang XIA
Clinical and Molecular Hepatology 2025;31(Suppl):S285-S300
Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.
4.Criteria and prognostic models for patients with hepatocellular carcinoma undergoing liver transplantation
Meng SHA ; Jun WANG ; Jie CAO ; Zhi-Hui ZOU ; Xiao-ye QU ; Zhi-feng XI ; Chuan SHEN ; Ying TONG ; Jian-jun ZHANG ; Seogsong JEONG ; Qiang XIA
Clinical and Molecular Hepatology 2025;31(Suppl):S285-S300
Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.
5.Metastasis patterns and survival analysis of 572 patients with metastatic cervical cancer:a hospital-based real world study
Jie SHEN ; Xiaoshuang FENG ; Hao WEN ; Changming ZHOU ; Miao MO ; Zezhou WANG ; Jing YUAN ; Xiaohua WU ; Ying ZHENG
China Oncology 2024;34(4):361-367
Background and purpose:Effective treatment for cervical cancer patients is one of the global strategies to eliminate cervical cancer.By analyzing the metastasis characteristics and survival status of patients with distant metastasis of cervical cancer from a hospital-based cancer registry data,our study provided real-world evidence for better survival of cervical cancer and finally eliminating cervical cancer.Methods:A total of 572 cervical cancer patients who had metastasis cancer at the initial diagnosis or developed distant metastasis during follow-up in Fudan University Shanghai Cancer Center from 2008 to 2017 were included in this study.Medical records review,telephone visits and death registry data linkage were applied in collecting endpoint data.The first follow-up date was the diagnose date of metastasis,and the last follow-up date was November 1,2020.Kaplan-Meier method was applied in evaluating the 1-,3-and 5-year overall survival(OS)rates for overall and site-specific patients.Results:The median follow-up time was 38.93 months,and 348 cases died during the follow-up.72.55%were single site metastasis,and 27.45%were multiple metastases.Among all metastatic sites,the proportion of lung metastasis was the highest,41.26%,15.21%to bone,and 11.54%to liver.After metastasis,the 1-year,3-year and 5-year OS rates were 62.29%(95%CI:62.25-62.33),33.13%(95%CI:33.08-33.18)and 23.42%(95%CI:23.37-23.47),respectively.In single site metastasis,1-year OS was the highest after metastasis to the lung(72.52%).Besides,there was no significant difference among different metastatic sites,both in 3-year and 5-year OS.Conclusion:The most frequent distant metastatic sites of cervical cancer are lung,bone and liver.The survival rate after metastasis is poor.Further research with systematic treatment strategy is required for better survival.
6.SWOT analysis of construction of intelligent vaccination clinics in Zhejiang Province
ZHENG Shuhan ; SHEN Lingzhi ; DENG Xuan ; SU Ying ; LUO Feng ; ZHOU Yang ; TANG Xuewen ; YAN Rui ; ZHU Yao ; HE Hanqing
Journal of Preventive Medicine 2024;36(8):669-673
Objective:
To analyze the strengths, weaknesses, opportunities and threats of the construction on intelligent vaccination clinics in Zhejiang Province, so as to provide countermeasures for promoting the construction of intelligent vaccination clinics in Zhejiang Province.
Methods:
By reviewing the annual reports of Zhejiang immunization planning, survey data from Zhejiang Centers for Disease Control and Prevention and Immunization Intelligent Service System, data of human resources of immunization planning, vaccine procurement, construction progress of intelligent vaccination clinics and vaccination were collected. The relevant literature was searched to gather information on the construction standards and norms of intelligent vaccination clinics. The analysis of the strengths, weaknesses, opportunities and threats (SWOT) of the construction of intelligent vaccination clinics was conducted, and corresponding countermeasures and suggestions were proposed.
Results:
The National Immunization Program reported vaccine rate in Zhejiang Province is more than 99%, and standardized vaccination clinics have been popularized throughout the province. The vaccination staff are professional, and a province-wide intelligent immunization service information system has been established, providing the resources and conditions for the construction of intelligent vaccination clinics. However, there are problems such as low data quality and matching efficiency in vaccination, insufficient data interoperability and sharing, unbalanced regional capabilities in intelligent transformation, and uneven distribution of talent and resources. It is crucial to seize the opportunities presented by the development of big data and artificial intelligence, rely on the regional development of the Internet and health industry, seize the opportunity of rapid growth in demand for intelligent vaccination services and high public acceptance, accelerate the construction of intelligent vaccination clinics, and establish intelligent vaccination service standards as soon as possible.
Conclusion
We should seize the opportunities presented by the digital reform and development, fully utilize the existing vaccination resources and strengths, address the shortcomings, and accelerate the construction of intelligent vaccination clinics in Zhejiang Province.
7.A multicenter study of neonatal stroke in Shenzhen,China
Li-Xiu SHI ; Jin-Xing FENG ; Yan-Fang WEI ; Xin-Ru LU ; Yu-Xi ZHANG ; Lin-Ying YANG ; Sheng-Nan HE ; Pei-Juan CHEN ; Jing HAN ; Cheng CHEN ; Hui-Ying TU ; Zhang-Bin YU ; Jin-Jie HUANG ; Shu-Juan ZENG ; Wan-Ling CHEN ; Ying LIU ; Yan-Ping GUO ; Jiao-Yu MAO ; Xiao-Dong LI ; Qian-Shen ZHANG ; Zhi-Li XIE ; Mei-Ying HUANG ; Kun-Shan YAN ; Er-Ya YING ; Jun CHEN ; Yan-Rong WANG ; Ya-Ping LIU ; Bo SONG ; Hua-Yan LIU ; Xiao-Dong XIAO ; Hong TANG ; Yu-Na WANG ; Yin-Sha CAI ; Qi LONG ; Han-Qiang XU ; Hui-Zhan WANG ; Qian SUN ; Fang HAN ; Rui-Biao ZHANG ; Chuan-Zhong YANG ; Lei DOU ; Hui-Ju SHI ; Rui WANG ; Ping JIANG ; Shenzhen Neonatal Data Network
Chinese Journal of Contemporary Pediatrics 2024;26(5):450-455
Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75%(27/36);boys accounted for 64%(23/36).Among the 36 neonates,31(86%)had disease onset within 3 days after birth,and 19(53%)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61%)had left cerebral infarction and 13(36%)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75%)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72%)and seizures in 10 neonates(34%).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33%,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44%(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.
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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