1.Expert Consensus on Clinical Diseases Responding Specifically to Traditional Chinese Medicine: Perimenopausal Syndrome
Shiwan HU ; Haiyan LIANG ; Kun MA ; Xiaona MA ; Zihan FANG ; Wenpei BAI ; Xinmin LIU ; Hongtian LI ; Fengmei LIAN ; Wei ZHANG ; Lihua QIN ; Min SHANG ; Ailuan LAI ; Xiuxiang TENG ; Mei MO ; Xiaoxiao ZHANG ; Linhua ZHAO
Chinese Journal of Experimental Traditional Medical Formulae 2024;30(21):234-242
Perimenopausal syndrome (MPS), a common endocrine system disease, is one of the diseases responding specifically to traditional Chinese medicine (TCM). The China Association of Chinese Medicine organized experts in endocrinology, gynecology, and interdisciplinary fields of both Western and Chinese medicine to discuss the advantages and challenges of diagnosing and treating MPS with Western medicine, TCM, and integrative medicine. Experts at the conference believe that MPS is initiated by estrogen decline and rooted in deficiency, with the pathogenesis being imbalance between Yin and Yang in the kidney. The hormone replacement therapy in Western medicine for menopause can rapidly alleviate related symptoms by quickly restoring the estrogen level and timely detect and delay complications of menopause, whereas such a therapy has certain risks, necessitating close monitoring of adverse reactions. Moreover, the various contraindications and precautions limit the clinical application of the hormone replacement therapy. TCM has advantages in synergistically alleviating symptoms such as hot flashes, sweating, sleep disorders, and emotional abnormalities of MPS without causing obvious adverse reactions. However, its efficacy is slower than the hormone replacement therapy, and the TCM evidence for preventing and treating complications of menopause remains unclear. Three suggestions were proposed for the future development of both Western and TCM for ameliorating MPS. First, an integrated diagnosis and treatment system for MPS with both Western and Chinese medicine should be established. Second, high-quality evidence-based interventions for MPS should be developed with TCM alone or in combination with Western medicine. Third, efforts should be made to promote the new TCM drug development and the interdisciplinary cooperation for treating MPS.
2.Analysis for clinicopathological and immunohistochemical characteristics of patients with meibomian gland carcinoma
Man NIU ; Ying ZHAO ; Fengmei CAI ; Yuanpeng LI ; Wei QIAN ; Huifang WANG
International Eye Science 2024;24(11):1842-1845
AIM: To explore the clinicopathological and immunohistochemistry(IHC)characteristics of meibomian gland carcinoma(MGC).METHODS: Patients who were pathologically diagnosed as MGC from January 1, 2015 to December 31, 2020 in our hospital were enrolled, and their clinicopathological information was retrospectively analyzed. Cancer tissues from all the cases were IHC stained. En Vision two-step method, DAB staining, as well as hematoxylin re-staining were applied in the IHC assay.RESULTS: A total of 50 patients with 21 males and 29 females(1:1.38)were enrolled in the study, ranging from 26 to 80 years old, with a median age of 60 years. The upper eyelid, which was the predilection site, accounting for 66%(33/50). Histopathologically, moderately or poorly differentiated was in the majority(35/50, 70%). The expression rates of IHC parameters of MGC patients were as follows: GATA-3(49/50, 98%), EMA(49/50, 98%), CAM5.2(42/50, 84%), AR(41/50, 82%), MSH2(50/50, 100%), MSH6(50/50, 100%), MLH1(50/50, 100%), PMS2(50/50, 100%), Ki67(positive, 50%-90%). All the patients were followed up for 12 to 72 mo, with 5 cases of recurrence and 0 deaths.CONCLUSION: Pathological diagnosis of MGC should focus on observing cancer cells' cytoplasm to find relevant clues for cortical gland differentiation. Comprehensive analysis of multiple indicators is required when using IHC to assist diagnosis. For most MGC cancer cells, positive expressions of GATA-3, EMA, AR, CAM5.2 and a high Ki67 proliferation index could be always found. In addition, screening for Muir-Torre syndrome related IHC indicators could be also performed in diagnosing MGC simultaneously.
3.Noninvasive diagnostic indicators for histologically defined immune tolerance state in patients with chronic HBV infection and establishment and assessment of related models
Xinyu DU ; Jia LI ; Bei JIANG ; Kunyu ZHAO ; Yue HU ; Fengmei WANG ; Fengmin LU
Journal of Clinical Hepatology 2024;40(12):2392-2398
ObjectiveThe natural history of chronic HBV infection often involves a histologically defined immune tolerance state, and once such immune tolerance state is broken, antiviral therapy should be initiated immediately. This study aims to investigate the correlation between immune-mediated liver injury and virological indicators for HBV and precisely identify the patients with a histologically defined immune tolerance state. MethodsThis study was conducted among 577 HBeAg-positive chronic hepatitis B (CHB) patients with HBV DNA >2×106 IU/mL who did not receive antiviral therapy in The Fifth Medical Center of PLA General Hospital, Tianjin Second People’s Hospital, Shanghai Ruijin Hospital, and Taizhou Hospital of Zhejiang Province from January 2010 to December 2022. Liver biopsy was performed to determine the extent of liver injury, and the serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and virological indicators were measured. The proportion of patients with a histologically defined immune tolerance state was analyzed based on the cut-off values of noninvasive indicators recommended in various guidelines, especially HBV load. In addition, a diagnostic model was established for the histologically defined immune tolerance state based on serum HBV DNA at the time when its correlation with liver immunopathological injury disappeared as the new threshold in combination with multiple indicators. The Mann-Whitney U test was used for comparison of continuous data between two groups, and the chi-square test was used for comparison of categorical data between two groups. The Spearman method was used for correlation analysis. The binary Logistic regression analysis was used to establish a multivariate diagnostic model; the area under the receiver operating characteristic curve (AUC) was used to investigate the diagnostic efficiency of different models, and the Z test was used for comparison of AUC. ResultsAmong the patients with an immune tolerance state defined by the noninvasive indicators in the Chinese guidelines (2022 edition), the EASL guidelines (2017 edition), the AASLD guidelines (2018 edition), and the APASL guidelines (2015 edition) for the prevention and treatment of CHB, the patients with a histologically defined immune tolerance state who met the definition in this article (HBV DNA>2×106 IU/mL) accounted for 47.0%, 38.5%, 36.0%, and 44.6%, respectively, which did not exceed 50%. When the threshold of serum HBV DNA increased to >2×108 IU/mL, although the correlation between immune-mediated liver injury and HBV DNA disappeared (r=-0.029, P=0.704), the patients with a histologically defined immune tolerance state reached only 52.0%. In the cohort of 251 HBeAg-positive patients with serum HBV DNA >1×108 IU/mL, there were significant differences in the levels of HBsAg, HBeAg, HBV DNA, ALT, and AST between the significant liver injury group with 140 children and the non-significant liver injury group with 111 patients (all P<0.05), and the multivariate binary Logistic regression analysis showed that AST, HBV DNA, and HBeAg were influencing factors for histologically defined immune tolerance state in patients (all P<0.05). Based on the above indicators and related clinical data, a predictive model was established as logit(P)=1.424-0.028×AST, with an AUC of 0.730, an optimal cut-off value of 30.5 U/L, a sensitivity of 52.8%, and a specificity of 84.1%. A total of 238 adult patients with chronic HBV infection who underwent liver biopsy in Taizhou Hospital of Zhejiang Province were enrolled as the validation cohort, and the analysis showed that the predictive model established in this study had a better efficiency than AST/ALT, FIB-4, and APRI, with an AUC of 0.698, 0.555, 0.518, and 0.373, respectively (all P<0.05). ConclusionFor HBeAg-positive patients with chronic HBV infection and HBV DNA>2×108 IU/mL, an AST level of >30.5 U/L might indicate the “breakdown” of histologically defined immune tolerance state.
4.Application of the integrated medical and industrial training model in the training of oncology talents from the perspective of new medical sciences
Guogui SUN ; Yanlei GE ; Huaiyong NIE ; Yaning ZHAO ; Haimei BO ; Fengmei XING ; Yating ZHAO ; Hongcan YAN
Clinical Medicine of China 2024;40(1):77-80
The medical-industrial fusion training model combines the knowledge and technology of medical and engineering disciplines in the training of oncology graduate students, which can help accurate diagnosis and treatment of tumors, promote cooperation and innovation in oncology research, as well as promote the cultivation and exchanges of composite and innovative medical talents in oncology, promote the innovation and development of oncology diagnostic and treatment technology, and improve the survival rate and quality of life of oncology patients. This paper discusses the application of medical-industrial fusion training model in the training of o ncology professionals, and explores the new teaching mode of medical-industrial fusion thinking in the cultivation of complex and innovative medical talents in oncology under the background of "new medical science".
5.The role of tofacitinib in early atherosclerosis in mice with systemic lupus erythematosus
Qu CHEN ; Fengmei GE ; Zhao LI ; Qiushuang ZHANG ; Xue WU ; Qi CHEN ; Saiqi LI ; Xuebin WANG ; Xiuqing YAN
Chinese Journal of Rheumatology 2024;28(2):106-112
Objective:To investigate the effect of tofacitinib on early atherosclerosis of patients with systemic lupus erythematosus and explore the possible relationship between lupus nephritis and early atherosclerosis of systemic lupus erythematosus.Methods:Sixteen 8-week-old female MRL/lpr mice with a body weight of 20~25 g were selected and randomly divided into the treatment group and placebo group, with 8 mice in each group. The treatment group diluted tofacitinib by normal saline, and given at a dose of 10 mg·kg -1·d -1, and the placebo group (starch tablets) administered the medication in the same way as the treatment group for a total of 8 weeks. The ELISA method was applied to detect serum anti-dsDNA antibody levels in the two groups of mice. Bradford method protein concentration was used to determine the level of urine protein in mice. Automatic biochemical analyzer was used to detect blood lipids, urea nitrogen, serum creatinine, complement C3, complement C4 levels. Western blotting was used to determine the protein expression levels of monocyte chemoattractant protein-1 (MCP-1), non-receptor protein tyrosine kinase family 1 (JAK1), signal transducer and activator of transcription 1 (STAT1) and signal transducer and activator of transcription 2 (STAT2) in aortic and kidney tissues. After the aortic arch section were prepared, oil red O was used to stain the sections, and the vascular plaque area and intimal thickness were evaluated by ImageJ software. The kidneys were dissected and stained with HE, and the active lesions of lupus nephritis were evaluated using the glomerular activity scoring system. SPSS 23.0 software was used for statistical analysis, in which the between-group comparison was performed using two independent samples t-test, and the correlation analysis was performed using the Spearman method. Results:①The serum anti-dsDNA antibody expression level in the treatment group [(5.2±1.0) U/ml] was lower than that in the placebo group [(6.9±1.2) U/ml], ( Z=-3.07, P=0.008), and the levels of complement C3 and complement C4 were higher than those in the placebo group [(293±10) mg/L vs. (260±19) mg/L, Z=2.72, P=0.017]; (16±6) mg/L vs. (8±9) mg/L, Z=3.78, P=0.006]. There was no significant difference in serum BUN and Scr between the treatment group and the placebo group [(10.6±0.7) mmol/L vs. (11.5±1.1) mmol/L, Z=-1.96, P=0.071; (17±5) μmol/L vs. (22±6) μmol/L, Z=-1.79, P=0.095]. ② Compared with the placebo group, the levels of LDL, TC and TG in the treatment group decreased [(0.83±0.15) mmol/L vs. (1.08±1.05) mmol/L, Z=-3.95, P=0.001; (2.90±0.08) mmol/L vs. (1.81±0.97) mmol/L, Z=-5.17, P=0.001; (1.10±0.08) mmol/L vs. (1.60±0.42) mmol/L, Z=-3.23, P=0.013], and HDL level increased [(2.02±0.99) mmol/L vs. (1.81±0.97) mmol/L, Z=4.42, P=0.001]. ③ Compared with the placebo group, the levels of aortic MCP-1, JAK1, STAT1 and STAT2 in the treatment group were reduced [(0.17±0.30) vs. (0.23±0.05), Z=-3.06, P=0.009; (0.83±0.09) vs. (1.05±0.19), Z=-3.07, P=0.008; (0.77±0.07) vs. (0.94±0.13), Z=-2.83, P=0.014; (0.70±0.07) vs. (0.82±0.09), Z=-2.83, P=0.013], the aortic plaque area and aortic intimal thickness were lower than those in the placebo group [(12±31) μm 2vs. (1 242±1 101) μm 2, Z=-3.12, P=0.016; (63±7) μm vs. (82.10±8.06) μm, Z=-5.13, P<0.001]. ④ Compared with the placebo group, the urine protein level and glomerulonephritis activity score in the treatment group were decreased [(0.08±0.03) mg/mL vs. (0.20±0.11) mg/mL, Z=-3.08, P=0.015; (1.79±0.38) vs. (2.79±0.14) points, Z=-7.08, P<0.001)], and renal tissue MCP-1, JAK1, STAT1.Compared with the placebo group, STAT2 levels were reduced [(0.364±0.040) vs. (0.425±0.021), Z=-3.85, P=0.003; (0.689±0.074) vs. (0.838±0.068), Z=-4.19, P=0.001; (0.508±0.070) vs. (0.646±0.019), Z=-2.85, P=0.015; (0.618±0.062) vs. (0.740±0.101), Z=-2.94, P=0.013. ⑤ The glomerular mobility scores of the two groups were positively correlated with LDL, TCHO, TG, aortic plaque area and aortic intimal thickness ( r=0.51, P=0.043; r=0.79, P<0.001; r=0.64, P=0.008; r=0.82, P<0.001; r=0.74, P=0.001), and negatively correlated with HDL ( r=-0.53, P=0.036). The urine protein levels in the two groups were positively correlated with LDL, TC, TG, aortic plaque area and aortic intimal thickness ( r=0.67, P=0.004; r=0.68, P=0.004; r=0.53, P=0.033; r=0.80, P<0.001; r=0.74, P=0.001), and negatively correlated with HDL ( r=-0.57, P=0.021). Conclusion:The severity of lupus nephritis is correlated with atherosclerosis and dyslipidemia in the early stage of systemic lupus erythematosus. Tofacitinib may reduce the degree of early arteriosclerosis and lupus nephritis in MRL/LPR mice, and reduce blood lipid levels, which may be effective in improving the prognosis of SLE and improving the survival rate of patients.
6.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.
7.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.
8.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.
9.Changing resistance profiles of Proteus,Morganella and Providencia in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yunmin XU ; Xiaoxue DONG ; Bin SHAN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Ping JI ; Fengbo 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 ; 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 ; Hongyan ZHENG ; 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 ; Wenhui HUANG ; 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(4):410-417
Objective To understand the changing distribution and antimicrobial resistance profiles of Proteus,Morganella and Providencia in hospitals across China from January 1,2015 to December 31,2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods Antimicrobial susceptibility testing was carried out following the unified CHINET protocol.The results were interpreted in accordance with the breakpoints in the 2021 Clinical & Laboratory Standards Institute(CLSI)M100(31 st Edition).Results A total of 32 433 Enterobacterales strains were isolated during the 7-year period,including 24 160 strains of Proteus,6 704 strains of Morganella,and 1 569 strains of Providencia.The overall number of these Enterobacterales isolates increased significantly over the 7-year period.The top 3 specimen source of these strains were urine,lower respiratory tract specimens,and wound secretions.Proteus,Morganella,and Providencia isolates showed lower resistance rates to amikacin,meropenem,cefoxitin,cefepime,cefoperazone-sulbactam,and piperacillin-tazobactam.For most of the antibiotics tested,less than 10%of the Proteus and Morganella strains were resistant,while less than 20%of the Providencia strains were resistant.The prevalence of carbapenem-resistant Enterobacterales(CRE)was 1.4%in Proteus isolates,1.9%in Morganella isolates,and 15.6%in Providencia isolates.Conclusions The overall number of clinical isolates of Proteus,Morganella and Providencia increased significantly in the 7-year period from 2015 to 2021.The prevalence of CRE strains also increased.More attention should be paid to antimicrobial resistance surveillance and rational antibiotic use so as to prevent the emergence and increase of antimicrobial resistance.
10.Changing distribution and resistance profiles of Klebsiella strains in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chuyue ZHUO ; Yingyi GUO ; Chao ZHUO ; 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 ; 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 ; Wenhui HUANG ; 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(4):418-426
Objective To understand the changing distribution and antimicrobial resistance profiles of Klebsiella strains in 52 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Antimicrobial susceptibility testing was carried out according to the unified CHINET protocol.The susceptibility results were interpreted according to the breakpoints in the Clinical & Laboratory Standards Institute(CLSI)M100 document.Results A total of 241,549 nonduplicate Klebsiella strains were isolated from 2015 to 2021,including Klebsiella pneumoniae(88.0%),Klebsiella aerogenes(5.8%),Klebsiella oxytoca(5.7%),and other Klebsiella species(0.6%).Klebsiella strains were mainly isolated from respiratory tract(48.49±5.32)%.Internal medicine(22.79±3.28)%,surgery(17.98±3.10)%,and ICU(14.03±1.39)%were the top 3 departments where Klebsiella strains were most frequently isolated.K.pneumoniae isolates showed higher resistance rate to most antimicrobial agents compared to other Klebsiella species.Klebsiella isolates maintained low resistance rates to tigecycline and polymyxin B.ESBLs-producing K.pneumoniae and K.oxytoca strains showed higher resistance rates to all the antimicrobial agents tested compared to the corresponding ESBLs-nonproducing strains.The K.pneumoniae and carbapenem-resistant K.pneumoniae(CRKP)strains isolated from ICU patients demonstrated higher resistance rates to majority of the antimicrobial agents tested than the strains isolated from non-ICU patients.The CRKP strains isolated from adult patients had higher resistance rates to most of the antimicrobial agents tested than the corresponding CRKP strains isolated from paediatric patients.Conclusions The prevalence of carbapenem-resistant strains in Klebsiella isolates increased greatly from 2015 to 2021.However,the Klebsiella isolates remained highly susceptible to tigecycline and polymyxin B.Antimicrobial resistance surveillance should still be strengthened for Klebsiella strains.

Result Analysis
Print
Save
E-mail