1.Analysis on Pharmacodynamic Material Basis and Mechanism of Famous Classical Formula Renshen Wuweizi Tang in Treatment of Spleen and Lung Qi Deficiency Syndrome
Shanshan LI ; Yute ZHONG ; Xiaomei XIANG ; Wei KANG ; Shufan ZHOU ; Ping WANG ; Haiyu XU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(8):31-39
ObjectiveBased on ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry(UPLC-Q-TOF-MS/MS), network pharmacology and molecular docking techniques, to explore the pharmacodynamic material basis and mechanism of Renshen Wuweizi Tang in treating spleen-lung Qi deficiency syndrome. MethodsThe chemical components in the decoction of Renshen Wuweizi Tang were systematically characterized and identified by UPLC-Q-TOF-MS/MS, and network pharmacology was used to screen potential active ingredients, collect component targets and gene sets related to spleen-lung Qi deficiency syndrome, and obtain protein interaction relationships through STRING. Cytoscape 3.9.1 was used to construct a "formula-syndrome" association network and calculate topological feature values. Gene ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were performed on core genes to explore potential pharmacodynamic links, the average shortest path between the formula-drug target network and the pharmacodynamic link gene network was calculated to discover dominant pharmacodynamic links, and MCODE plugin was used to identify core gene clusters from the dominant pharmacodynamic links, which were validated using Gene Expression Omnibus(GEO), and molecular docking was performed between key components and core targets. ResultsOne hundred and thirty-seven components were identified in the negative ion mode, and eighty components were identified in the positive ion mode. After deduplication, a total of 185 components were identified, mainly composed of triterpenoid saponins(49) and flavonoids(54). Based on the "formula-syndrome" correlation network analysis, energy metabolism was determined to be the dominant pharmacodynamic link of Renshen Wuweizi Tang in the treatment of spleen-lung Qi deficiency syndrome. The results of molecular docking showed that 7 components(adenosine, atractylenolide Ⅱ, atractylenolide Ⅲ, ginsenoside Rg1, glycyrrhizin B2, glycyrrhizin E2 and campesterol) from 4 medicinal materials(Ginseng Radix et Rhizoma, Atractylodis Macrocephalae Rhizoma, Glycyrrhizae Radix et Rhizoma and Poria) in this formula might regulate energy metabolism by acting on 6 targets, namely cyclic adenosine monophosphate-response element binding protein 1(CREB1), glyceraldehyde-3-phosphate dehydrogenase(GAPDH), interleukin(IL)-6, nuclear transcription factor(NF)-κB1, peroxisome proliferator-activated receptor α(PPARα), and tumor necrosis factor(TNF), thus improving the symptoms of diseases related to spleen-lung Qi deficiency syndrome. ConclusionThis study established a UPLC-Q-TOF-MS/MS for rapid characterization and identification of chemical components in the decoction of Renshen Wuweizi Tang, expanding the understanding of the material composition of this formula, and found that 7 components might act on the key advantageous pharmacodynamic link "energy metabolism" through 6 targets to improve the related symptoms of spleen-lung Qi deficiency syndrome. This can provide a reference for the subsequent exploration of the material benchmark and mechanism of the famous classical formula.
2.Theoretical Exploration of Same "Etiology-Mechanism-Syndrome-Treatment-Prevention" in Insomnia and Skin Aging
Bo XU ; Miao ZHU ; Kang SUN ; Yuan PENG ; Ping WANG ; Li YANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(10):72-78
Sleep, skin, and health are closely interconnected. Clinically, insomnia has a high incidence and is often accompanied by or secondary to skin aging. The two conditions exhibit "different diseases with the same syndrome", significantly affecting the physical and mental health of the Chinese population. Preventing and treating skin aging by improving insomnia is an important strategy, with the principle of "treating different diseases with the same approach" serving as a crucial therapeutic guideline. However, effective clinical prevention and treatment methods for both conditions remain lacking. Traditional Chinese medicine (TCM) has a profound theoretical foundation and notable efficacy in the concurrent treatment of insomnia and skin aging, yet there are few reports on the etiology, pathogenesis, therapeutic principles, and treatment methods of their shared treatment, warranting further exploration. Based on holistic view and syndrome differentiation and treatment in TCM, this study systematically investigates the theoretical origins of the shared manifestations of insomnia and skin aging from multiple dimensions, including etiology, pathological location, pathogenesis, disease nature, and prevention and treatment strategies. As early as Huangdi's Internal Classic (Huangdi Neijing), it was recognized that mental clarity during the day, sound sleep at night, and firm, healthy skin are key indicators of external health, whereas daytime lethargy, poor sleep quality, and dry, withered skin are prominent signs of aging. Maintaining mental clarity during the day and restful sleep at night is essential for skin integrity and healthy aging. Later medical scholars proposed that the common etiology of insomnia and skin aging lies in "internal-external interactions", with the pathological location involving "the five organ systems". The primary pathogenesis includes "deficiency, fire, stagnation, phlegm, and blood stasis", while the disease nature is often characterized by "a combination of deficiency and excess". Treatment should be guided by syndrome differentiation, following the principle of balancing Yin and Yang. This theoretical exploration enriches and advances TCM understanding of disease onset and prevention, providing theoretical guidance for the clinical prevention and treatment of insomnia-associated skin aging and contributing to the realization of the "Healthy China" initiative.
3.Preliminary exploration of the pharmacological effects and mechanisms of icaritin in regulating macrophage polarization for the treatment of intrahepatic cholangiocarcinoma
Jing-wen WANG ; Zhen LI ; Xiu-qin HUANG ; Zi-jing XU ; Jia-hao GENG ; Yan-yu XU ; Tian-yi LIANG ; Xiao-yan ZHAN ; Li-ping KANG ; Jia-bo WANG ; Xin-hua SONG
Acta Pharmaceutica Sinica 2024;59(8):2227-2236
The incidence of intrahepatic cholangiocarcinoma (ICC) continues to rise, and there are no effective drugs to treat it. The immune microenvironment plays an important role in the development of ICC and is currently a research hotspot. Icaritin (ICA) is an innovative traditional Chinese medicine for the treatment of advanced hepatocellular carcinoma. It is considered to have potential immunoregulatory and anti-tumor effects, which is potentially consistent with the understanding of "Fuzheng" in the treatment of tumor in traditional Chinese medicine. However, whether ICA can be used to treat ICC has not been reported. Therefore, in this study, sgp19/kRas, an
4.Transcutaneous Electrical Acupoint Stimulation Promotes PGC-1α Mediated Mitochondrial Biogenesis and Antioxidant Stress to Protect Cognitive Function in Vascular Dementia Rats
Ji-Liang KANG ; Ke HU ; Jun-Yue LU ; Zi-Wei HU ; Biao-Ping XU ; Xiao-Mao LI ; Jun-Jie ZHOU ; Yu JIN ; Min TANG ; Rong XU ; You-Liang WEN
Progress in Biochemistry and Biophysics 2024;51(5):1191-1202
ObjectiveThe purpose of this study was to investigate the effects of transcutaneous electrical acupoint stimulation (TEAS) on cognitive function of vascular dementia (VD) rats and its mechanism. MethodsVD rat model was established by modified two-vessel occlusion (2-VO). After modeling, TEAS and electroacupuncture (EA) were used to stimulate Baihui and Zusanli points of rats respectively for 14 d. After treatment, novel object recognition test, Morris water maze test, and Y maze test were used to evaluate the spatial memory and learning ability of rats. Hematoxylin and eosin staining was used to observe the morphology of hippocampal neurons. Transmission electron microscopy was used to observe the ultrastructure of hippocampal mitochondria. Enzyme-linked immunosorbent assay kits were used to detected the levels of SOD, CAT, GSH-Px, MDA and ROS in serum of rats. Western blot was used to detect the expression of PGC-1α, TFAM, HO-1, NQO1 proteins in the hippocampus, Keap1 protein in the cytoplasm and Nrf2, NRF1 proteins in the nucleus. ResultsAfter treatment for 14 d, compared to the model group, the escape latency of VD rats decreased, while the discrimination index, the times of rats crossing the original platform area, the residence time in the original platform quadrant, and the percentage of alternation increased. TEAS can improve the structure of hippocampal neurons and mitochondria of VD rats, showing that neurons were arranged more regularly and distributed more evenly, nuclear membrane and nucleoli were clearer, and mitochondrial swelling were reduced, mitochondrial matrix density were increased, and mitochondrial cristae were more obvious. The levels of SOD, GSH-Px and CAT in serum increased significantly, while the concentration of MDA and ROS decreased. TEAS also up-regulated the expression levels of PGC-1α TFAM, NQO1 and HO-1 proteins in the hippocampus and Nrf2, NRF1 proteins in the nucleus, but down-regulated the Keap1 protein in the cytoplasm. ConclusionTEAS can improve cognition, hippocampal neurons and mitochondrial structure of VD rats, and the effect is better than EA. The mechanism may be the activation of PGC-1α mediated mitochondrial biogenesis and antioxidant stress, which also provides a potential therapeutic technology and experimental basis for the treatment of VD.
5.Risk factors and mortality for carbapenem-resistant Acinetobacter baumannii bloodstream infection in elderly patients:a 10-year retrospective study
Ye XUE ; Chao-Shi ZOU ; Tai-Jie LI ; Mei-Xiang QIN ; Chan LIANG ; Kang-Hai LIU ; Dan-Ping QIU
Chinese Journal of Infection Control 2024;23(2):155-161
Objective To assess the risk factors for carbapenem-resistant Acinetobacter baumannii(CRAB)bloodstream infection(BSI)and 28-day short-term mortality in elderly patients,and provide reference for the pre-vention and treatment of CRAB BSI.Methods Clinical data of patients aged ≥60 years and diagnosed with AB BSI in a hospital in Yulin City from January 2013 to December 2022 were retrospectively analyzed,including demogra-phic and microbiological characteristics,as well as clinical outcomes of the patients.Variables which were significant in univariate analysis were selected for multivariate analysis using binary logistic regression model and Cox propor-tional hazards model.Independent risk factors for infection were further determined,and survival analysis was per-formed using Kaplan-Meier curve.Results A total of 150 patients were included in the study,out of which 16 pa-tients(10.7%)had CRAB BSI and 134 had carbapenem-sensitive AB(CSAB)BSI.The 28-day short-term mortali-ty of AB BSI in elderly patients was 15.3%(23/150,95%CI:9.6%-21.1%),and the short-term mortality of CRAB BSI was higher than that of CSAB([56.3%,9/16]vs[10.4%,14/134]).Deep venous catheterization(OR:15.598,95%CI:1.831-132.910)and combined infections of other sites(OR:15.449,95%CI:1.497-159.489)were related to CRAB BSI in elderly patients.The independent risk factors for 28-day mortality in elderly patients with AB BSI were hemodialysis(OR:11.856,95%CI:2.924-48.076),intensive care unit admission(OR:9.387,95%CI:1.941-45.385),and pulmonary infection being suspected source of bacteremia(OR:7.019,95%CI:1.345-36.635).Conclusion The occurrence of CRAB BSI in elderly patients is related to the combined infection of other sites and deep vein catheterization.Hemodialysis,admission to ICU,and pulmonary infection being suspected source of bacteremia are independent risk factors for the prognosis of AB BSI in elderly patients.
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.Development and validation of dynamic prediction models using vital signs time series data for fatal massive hemorrhage in trauma
Cheng-Yu GUO ; Ming-Hui GONG ; Qiao-Chu SHEN ; Hui HAN ; Ruo-Lin WANG ; Hong-Liang ZHANG ; Jun-Kang WANG ; Chun-Ping LI ; Tan-Shi LI
Medical Journal of Chinese People's Liberation Army 2024;49(6):629-635
Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.
8.Investigation on risk factors for clinical outcomes of patients with bloodstream infections in the emergency intensive care unit
Pei ZHANG ; Ping TAI ; Kang LIN ; Wei LI ; Ling JIN ; Bangshun HE ; Xin LIN
Chinese Journal of Clinical Laboratory Science 2024;42(5):332-336
Objective To investigate the risk factors for the clinical outcomes of patients with bloodstream infections in emergency in-tensive care unit(EICU)and provide a basis for clinical treatment.Methods The medical records and blood culture records of 141 patients with bloodstream infections in the EICU of our hospital from January 2019 to April 2023 were retrospectively collected.The risk factors leading to patients′death were analyzed by the Logistic regression and the relationships between these factors and patients′sur-vival time and outcomes were evaluated by the Cox regression.Results Among the 141 patients with bloodstream infections in the EICU,the mixed bloodstream infections of two or more bacteria(odds ratio[OR]=5.68,95%confidence interval[CI]:1.20-26.98,P<0.05)and bloodstream infections of multidrug-resistant bacteria(OR=6.39,95%CI:2.78-14.67,P<0.01)were significantly cor-related with the patients′death.Whether to adjust medication in a timely manner based on drug sensitivity results(hazard ratio[HR]=0.47,95%CI:0.30-0.74)and bloodstream infections of multidrug-resistant bacteria(HR=2.02,95%CI:1.28-3.20)were the risk factors leading to the death of patients with bloodstream infections in the EICU(P<0.01).Conclusion Early blood culture to identify the pathogenic bacteria and precise medication to control infection can effectively reduce the mortality of patients with bloodstream in-fections in the EICU.
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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