1.Development and application on a full process disease diagnosis and treatment assistance system based on generative artificial intelligence.
Wanjie YANG ; Hao FU ; Xiangfei MENG ; Changsong LI ; Ce YU ; Xinting ZHAO ; Weifeng LI ; Wei ZHAO ; Qi WU ; Zheng CHEN ; Chao CUI ; Song GAO ; Zhen WAN ; Jing HAN ; Weikang ZHAO ; Dong HAN ; Zhongzhuo JIANG ; Weirong XING ; Mou YANG ; Xuan MIAO ; Haibai SUN ; Zhiheng XING ; Junquan ZHANG ; Lixia SHI ; Li ZHANG
Chinese Critical Care Medicine 2025;37(5):477-483
The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence
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Humans
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Delivery of Health Care
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Generative Artificial Intelligence
2.Novel mutations of AMHR2 in two families with persistent Müllerian duct syndrome
Lixia WANG ; Xiaoyu LI ; Yaru XU ; Jingzi WANG ; Haobo ZHU ; Jun DONG ; Yunfei GUO ; Yongji DENG
Chinese Journal of Applied Clinical Pediatrics 2024;39(6):465-468
Persistent Müllerian duct syndrome(PMDS) is a rare disorder that arises from a lack of active anti-Müllerian hormone(AMH) or type Ⅱ AMH receptor(AMHR2) deficiency in males with a normal 46, XY chromosome karyotype.It presents that the external genitalia appears normally while the Müllerian duct structure(uterus, fallopian tubes, upper vagina) persists in the body.Common pathogenic factors are mutations in the AMH and AMHR2 genes, inherited in an autosomal recessive manner.This study reported two families with PMDS.The first patient was diagnosed with PMDS due to cryptorchidism in May 2019.Gene sequencing analysis revealed a new missense mutation(c.579G>T; p.W193C) and a splicing mutation(c.622-3C>A; splicing) in the AMHR2 gene.His father had the missense mutation(c.579G>T; p.W193C), and his mother had the splicing mutation(c.622-3C>A; splicing).The second patient was diagnosed with PMDS due to bilateral cryptorchidism, transverse testis ectopia in the right testicle in March 2023.Undegraded Müllerian tube derivatives were found between the two testicles, and serum AMH levels were very high(565.00 μg/L).Gene sequencing analysis reported that the AMHR2 gene had a new deletion mutation(c.835_837del; p.Leu279del).Both his father and mother had a deletion mutation(c.835_837del; p.Leu279del).This study reports two new AMHR2 gene mutations that expand the mutation sites of this rare disease.It is recommended to consider PMDS in the differential diagnosis of cryptorchidism, undergo surgery as early as possible, and treat Müllerian duct derivatives based on individual anatomical characteristics.
3.Potential Mechanism of Taraxaci Herba Against Bladder Cancer: A Review
Mingshun ZUO ; Zhicheng DONG ; Yu ZUO ; Hongchuan CHEN ; Hongjia CAI ; Congcong WU ; Xiaoyu AI ; Neng ZHANG
Chinese Journal of Experimental Traditional Medical Formulae 2024;30(7):290-298
Bladder cancer (BCa) is the most common malignant tumor of the urinary system, and its incidence is increasing year by year. At present, for all patients with resectable non-metastatic muscle-invasive BCa, radical cystectomy + bilateral pelvic lymph node dissection is strongly recommended, but they still face the risk of recurrence, metastasis and death. In recent years, the proportion of patients with advanced and metastatic BCa is increasing among patients with newly diagnosed BCa. Although current treatment models are diverse, they often struggle to achieve significant efficacy due to their low effectiveness and adverse effects, resulting in low survival rates for patients with advanced and metastatic BCa. Therefore, the treatment of BCa still faces great challenges, and there is an urgent need to discover an effective new antitumor drug. With the improvement of medical standards, traditional Chinese medicine has shown great advantages in the treatment of BCa. Traditional Chinese medicine is mild and easy to accept, and can inhibit tumor progression through a multi-pathway, multi-way and multi-target manner, so as to exert its anticancer effect. Taraxaci Herba is a medicinal and food homologous plant, which has many biological activities, such as antibacterial, anti-inflammatory, anti-oxidation, anti-tumor, protecting liver and gallbladder, reducing blood sugar and enhancing immunity, and it has shown a clear anticancer effect in breast cancer, liver cancer, gastric cancer, tongue cancer and lung cancer. By reviewing previous studies worldwide, this article summarizes the mechanism of Taraxaci Herba extract in inducing autophagy and apoptosis, inhibiting cell migration and invasion, regulating cell cycle and proliferation, regulating cell metabolism, inhibiting tumor angiogenesis, combining the effects of chemotherapeutic drugs, and regulating the transduction of related signal pathways. On this basis, this study systematically elaborates on the potential mechanism of Taraxaci Herba against BCa, in order to provide a theoretical basis for the research and treatment of BCa.
4.Effect of Modified Dahuang Huanglian Xiexintang on Oxidative Stress Injury of Liver in Type 2 Diabetes Mellitus Rats Based on Nrf2/HO-1 Axis
Chengjun MA ; Fengzhe YAN ; Lixia YANG ; Yonglin LIANG ; Xiangdong ZHU ; Dong AN ; Yankui GAO
Chinese Journal of Experimental Traditional Medical Formulae 2024;30(24):121-130
ObjectiveTo explore the effects and mechanisms of modified Dahuang Huanglian Xiexintang on hepatic oxidative stress injury in type 2 diabetes mellitus (T2DM) rats based on the nuclear factor erythroid 2 related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) axis. MethodSix ZDF (fa/+) rats were as assigned to the blank group, and 30 ZDF (fa/fa) rats were used to induce the T2DM model by feeding a high-fat diet. After successful modeling, the rats were randomly divided into the model group, metformin group (0.18 g·kg-1), and low, medium, and high dose groups of modified Dahuang Huanglian Xiexintang (0.54, 1.08, 2.16 g·kg-1), with six rats in each group. After 12 weeks of drug intervention, the body mass, liver mass, fasting blood glucose (FBG), and oral glucose tolerance test (OGTT) levels were measured. Serum total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) levels were detected using an automatic biochemical analyzer. The pathological changes of liver tissue were observed by hematoxylin-eosin (HE) staining. Enzyme-linked immunosorbent assay (ELISA) was used to detect the activity of superoxide dismutase (SOD), reactive oxygen species (ROS), glutathione peroxidase (GSH-Px), and the level of malondialdehyde (MDA) in liver tissues. Immunohistochemistry was used to detect the expression of Nrf2 in the liver. Real time quantitative polymerase chain reaction (Real-time PCR) and Western blot were used to detect the mRNA and protein expression levels of Nrf2 and HO-1 in liver tissues. ResultCompared with the normal group, the model group showed a significant increase in body mass, liver mass, and liver index (P<0.01). Compared with the model group, the metformin group and the medium and high dose groups of modified Dahuang Huanglian Xiexintang showed a significant decrease in body weight, liver mass, and liver index (P<0.01). Compared with the normal group, the model group showed significantly increased TC, TG, and LDL levels (P<0.01), and significantly decreased HDL levels (P<0.01). Compared with the model group, the metformin group and all doses of modified Dahuang Huanglian Xiexintang showed significantly reduced TC levels (P<0.01), and significantly reduced TG levels (P<0.05). The medium and high dose groups of modified Dahuang Huanglian Xiexintang showed significantly reduced LDL levels (P<0.05). The metformin group and all doses of modified Dahuang Huanglian Xiexintang showed significantly increased HDL levels (P<0.05). Compared with the normal group, the model group showed significantly increased ALT and AST activities (P<0.01). Compared with the model group, all doses of modified Dahuang Huanglian Xiexintang and the metformin group showed significantly reduced ALT activities (P<0.05) and significantly reduced AST activities (P<0.01). Compared with normal group, the model group showed significantly increased FBG at all time points (P<0.01). Compared with the model group, the metformin group and all doses of modified Dahuang Huanglian Xiexintang showed significantly reduced FBG at 8, 10, 12 weeks. The OGTT results showed that compared with the normal group, the model group had significantly increased blood glucose at all time points (P<0.01). Compared with the model group, the metformin group showed significantly reduced blood glucose at all time points (P<0.01), and the medium and high dose groups of modified Dahuang Huanglian Xiexintang showed significantly reduced blood glucose at 90, 120 min (P<0.01). HE pathology showed clear and regular liver cell structure in the normal group, while the model group showed disordered liver cell structure with visible fat vacuoles and a large number of deformed necrotic cells. The liver tissue structure improved in the metformin group and all doses of modified Dahuang Huanglian Xiexintang, with fewer necrotic cells. Compared with the normal group, the model group showed significantly reduced SOD and GSH-Px levels (P<0.01), and significantly increased ROS and MDA levels (P<0.01). Compared with the model group, the metformin group and all doses of modified Dahuang Huanglian Xiexintang showed significantly increased SOD and GSH-Px levels (P<0.01), and significantly reduced MDA levels (P<0.01). The medium and high dose groups of modified Dahuang Huanglian Xiexintang showed significantly reduced ROS levels (P<0.05). Compared with the normal group, the model group showed significantly reduced Nrf2 and HO-1 mRNA expression levels (P<0.01). Compared with the model group, the metformin group and the medium and high dose groups of modified Dahuang Huanglian Xiexintang showed significantly increased Nrf2 and HO-1 mRNA expression levels (P<0.05). Immunohistochemistry showed that compared with the normal group, the model group had significantly reduced positive expression of Nrf2 and HO-1 (P<0.05). Compared with the model group, the metformin group and all doses of modified Dahuang Huanglian Xiexintang showed increased positive expression of Nrf2 and HO-1, with a significant increase in brown-yellow granules around the cell nucleus (P<0.05). Western blot results showed that compared with the normal group, the model group had significantly reduced protein expression of Nrf2 and HO-1 (P<0.01). Compared with the model group, the metformin group and all doses of modified Dahuang Huanglian Xiexintang showed significantly increased protein expression of Nrf2 and HO-1 (P<0.01). ConclusionModified Dahuang Huanglian Xiexintang can significantly improve the general condition and pathological changes of liver tissues in T2DM model rats. This improvement is likely achieved through ameliorating hepatic oxidative stress injury via regulating the Nrf2/HO-1 axis.
5.Research Progress on Mechanisms and Optimization Methods for Toxicity Induced by Antibody-Drug Conjugates
Yanli JIA ; Xiaoyu LI ; Houwu FAN ; Wenqing DUAN ; Lixia HU ; Jian ZHOU ; Fengming RAN ; Shuang DONG
Cancer Research on Prevention and Treatment 2024;51(7):606-612
Since the approval of gemtuzumab ozogamicin,an antibody-drug conjugate(ADC)targeting CD33 in 2000,13 ADC drugs have been approved by the FDA.Although these drugs have clearly improved the survival of patients with various types of advanced cancers,their significant toxicity has compromised their therapeutic benefits.The adverse reactions of ADC drugs are complex and include on-target and off-target toxicities,where the payload drug is a determining factor.Antibody and linker may also affect the degree of toxicity.Combination therapy becomes an important strategy in anticancer treatment because of its increased efficiency,but treatment-related adverse reactions also increase accordingly.This review comprehensively analyzes the toxicity mechanisms of current ADC drugs and proposes various optimization strategies,including but not limited to optimizing linker molecules,upgrading antibody design,and changing drug administration strategies,to improve the overall safety profile of ADC drugs.
6.National bloodstream infection bacterial resistance surveillance report (2022) : Gram-negative bacteria
Zhiying LIU ; Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Haifeng MAO ; Hui DING ; Pengpeng TIAN ; Jiangqin SONG ; Yongyun LIU ; Jiliang WANG ; Yan JIN ; Yuanyuan DAI ; Yizheng ZHOU ; Yan GENG ; Fenghong CHEN ; Lu WANG ; Yanyan LI ; Dan LIU ; Peng ZHANG ; Junmin CAO ; Xiaoyan LI ; Dijing SONG ; Xinhua QIANG ; Yanhong LI ; Qiuying ZHANG ; Guolin LIAO ; Ying HUANG ; Baohua ZHANG ; Liang GUO ; Aiyun LI ; Haiquan KANG ; Donghong HUANG ; Sijin MAN ; Zhuo LI ; Youdong YIN ; Kunpeng LIANG ; Haixin DONG ; Donghua LIU ; Hongyun XU ; Yinqiao DONG ; Rong XU ; Lin ZHENG ; Shuyan HU ; Jian LI ; Qiang LIU ; Liang LUAN ; Jilu SHEN ; Lixia ZHANG ; Bo QUAN ; Xiaoping YAN ; Xiaoyan QI ; Dengyan QIAO ; Weiping LIU ; Xiusan XIA ; Ling MENG ; Jinhua LIANG ; Ping SHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2024;17(1):42-57
Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System(BRICS)were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period,9 035 strains of Gram-negative bacteria were collected from 51 hospitals,of which 7 895(87.4%)were Enterobacteriaceae and 1 140(12.6%)were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli( n=4 510,49.9%), Klebsiella pneumoniae( n=2 340,25.9%), Pseudomonas aeruginosa( n=534,5.9%), Acinetobacter baumannii complex( n=405,4.5%)and Enterobacter cloacae( n=327,3.6%). The ESBLs-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus spp. were 47.1%(2 095/4 452),21.0%(427/2 033)and 41.1%(58/141),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(58/4 510)and 13.1%(307/2 340);62.1%(36/58)and 9.8%(30/307)of CREC and CRKP were resistant to ceftazidime/avibactam combination,respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 59.5%(241/405),while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 18.4%(98/534). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions,with statistically significant differences in the prevalence of CRKP and CRPA( χ2=20.489 and 20.252, P<0.001). The prevalence of CREC,CRKP,CRPA,CRAB,ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals( χ2=11.953,81.183,10.404,5.915,12.415 and 6.459, P<0.01 or <0.05),while the prevalence of CRPA was higher in economically developed regions(per capita GDP ≥ 92 059 Yuan)than that in economically less-developed regions(per capita GDP <92 059 Yuan)( χ2=6.240, P=0.012). Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend,and Escherichia coli is ranked in the top,while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different,and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.
7.National bloodstream infection bacterial resistance surveillance report(2022): Gram-positive bacteria
Chaoqun YING ; Yunbo CHEN ; Jinru JI ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Haifeng MAO ; Hui DING ; Pengpeng TIAN ; Jiangqin SONG ; Yongyun LIU ; Jiliang WANG ; Yan JIN ; Yuanyuan DAI ; Yizheng ZHOU ; Yan GENG ; Fenghong CHEN ; Lu WANG ; Yanyan LI ; Dan LIU ; Peng ZHANG ; Junmin CAO ; Xiaoyan LI ; Dijing SONG ; Xinhua QIANG ; Yanhong LI ; Qiuying ZHANG ; Guolin LIAO ; Ying HUANG ; Baohua ZHANG ; Liang GUO ; Aiyun LI ; Haiquan KANG ; Donghong HUANG ; Sijin MAN ; Zhuo LI ; Youdong YIN ; Kunpeng LIANG ; Haixin DONG ; Donghua LIU ; Hongyun XU ; Yinqiao DONG ; Rong XU ; Lin ZHENG ; Shuyan HU ; Jian LI ; Qiang LIU ; Liang LUAN ; Jilu SHEN ; Lixia ZHANG ; Bo QUAN ; Xiaoping YAN ; Xiaoyan QI ; Dengyan QIAO ; Weiping LIU ; Xiusan XIA ; Ling MENG ; Jinhua LIANG ; Ping SHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2024;17(2):99-112
Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-positive bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-positive bacteria from blood cultures in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System(BRICS)were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:A total of 3 163 strains of Gram-positive pathogens were collected from 51 member units,and the top five bacteria were Staphylococcus aureus( n=1 147,36.3%),coagulase-negative Staphylococci( n=928,29.3%), Enterococcus faecalis( n=369,11.7%), Enterococcus faecium( n=296,9.4%)and alpha-hemolyticus Streptococci( n=192,6.1%). The detection rates of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)were 26.4%(303/1 147)and 66.7%(619/928),respectively. No glycopeptide and daptomycin-resistant Staphylococci were detected. The sensitivity rates of Staphylococcus aureus to cefpirome,rifampin,compound sulfamethoxazole,linezolid,minocycline and tigecycline were all >95.0%. Enterococcus faecium was more prevalent than Enterococcus faecalis. The resistance rates of Enterococcus faecium to vancomycin and teicoplanin were both 0.5%(2/369),and no vancomycin-resistant Enterococcus faecium was detected. The detection rate of MRSA in southern China was significantly lower than that in other regions( χ2=14.578, P=0.002),while the detection rate of MRCNS in northern China was significantly higher than that in other regions( χ2=15.195, P=0.002). The detection rates of MRSA and MRCNS in provincial hospitals were higher than those in municipal hospitals( χ2=13.519 and 12.136, P<0.001). The detection rates of MRSA and MRCNS in economically more advanced regions(per capita GDP≥92 059 Yuan in 2022)were higher than those in economically less advanced regions(per capita GDP<92 059 Yuan)( χ2=9.969 and 7.606, P=0.002和0.006). Conclusions:Among the Gram-positive pathogens causing bloodstream infections in China, Staphylococci is the most common while the MRSA incidence decreases continuously with time;the detection rate of Enterococcus faecium exceeds that of Enterococcus faecalis. The overall prevalence of vancomycin-resistant Enterococci is still at a low level. The composition ratio of Gram-positive pathogens and resistant profiles varies slightly across regions of China,with the prevalence of MRSA and MRCNS being more pronounced in provincial hospitals and areas with a per capita GDP≥92 059 yuan.
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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