1.Guangxi expert consensus on rapid comprehensive evaluation of oral dihydropyridine calcium channel blockers in the treatment of cardiovascular disease
Siru ZHOU ; Yue QIU ; Weipei SHEN ; Zhenguang HUANG ; Xiaoyu CHEN ; Hongliang ZHANG
China Pharmacy 2025;36(7):769-778
OBJECTIVE To conduct a rapid and comprehensive evaluation of commonly used oral dihydropyridine calcium channel blockers (DHP CCBs) in Guangxi, and provide scientific basis for clinical medication and drug selection in medical institutions. METHODS Based on the actual drug use data of public medical institutions at the second level and above in Guangxi Zhuang Autonomous Region, and based on the national centralized collection catalog, commonly used oral DHP CCBs were selected. The Professional Committee of Evidence-based Pharmacy of the Guangxi Pharmaceutical Association organized relevant experts from multiple medical institutions in the region to conduct a quantitative scoring of the selected oral DHP CCBs from five key dimensions of pharmaceutical characteristics, effectiveness, safety, economy, and other attributes, by referring to the Quick Guideline for Drug Evaluation and Selection in Chinese Medical Institutions (the Second Edition), combined with the latest evidence-based medical research results, and widely soliciting suggestions from clinical and pharmaceutical experts. Finally, the Guangxi Expert Consensus on Rapid Comprehensive Evaluation of Oral Dihydropyridine Calcium Channel Blockers in the Treatment of Cardiovascular Disease was formulated. RESULTS A total of 30 commonly used oral DHP CCBs were selected. Among them, Amlodipine besylate tablets (Huizhi) demonstrated superior comprehensive performance (81.79 points), excelling particularly in pharmaceutical properties, effectiveness and other attributes. The compound scores of Amlodipine besylate tablets (Chongqing Yaoyou) and Amlodipine besylate tablets (Suzhou Dongrui) ranked second and third respectively, with scores of 81.66 and 81.60 points. CONCLUSIONS This consensus can provide guidance and decision-making support for the rational clinical application of oral DHP CCBs in Guangxi Region and the selection of drug directories in medical institutions.
2.Timosaponin BⅡ Combined with Icariin Maintains Osteoclast-osteoblast Coupling by Restoring Yin-Yang Balance
Zaishi ZHU ; Zeling HUANG ; Weiye CAI ; Hua CHEN ; Boen SONG ; Yue LU ; Qing LU ; Xiaofeng SHEN
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(18):48-57
ObjectiveTo explore the effect of timosaponin BⅡ (TBⅡ) combined with icariin (ICA) on osteoclast (OC)-osteoblast (OB) coupling and decipher the mechanism from the cellular level. MethodsThe cell counting kit-8 (CCK-8) was used to assess the effects of different concentrations of TBⅡ and different concentrations of TBⅡ+ICA on the growth of RAW264.7 cells. Soluble receptor activator of nuclear factor-κB ligand (sRANKL) was used to induce the differentiation of RAW264.7 pre-osteoclasts into osteoclasts. The cells were allocated into sRANKL, TBⅡ (1, 5, 10 μmol·L-1), and TBⅡ+ICA groups. Tartrate-resistant acid phosphatase staining was performed to assess the effects of TBⅡ and TBⅡ+ICA on osteoclast differentiation. Real-time quantitative polymerase chain reaction (Real-time PCR) was conducted to examine the effects of TBⅡ+ICA on the expression of key genes involved in osteoclast differentiation and osteoclast-derived coupling factors. The osteogenic differentiation conditioned medium mixed with osteoclast supernatant was used to induce osteogenic differentiation of MC3T3-E1 cells. Alkaline phosphatase staining and alizarin red S staining were employed to determine the effect of TBⅡ+ICA on osteogenic differentiation. Real-time PCR was employed to evaluate the effects of conditioned medium on key genes involved in osteogenic differentiation. ResultsTBⅡ at 1, 5, 10 μmol·L-1 had no significant effect on the cell survival rate. Compared with the sRANKL group, TBⅡ inhibited osteoclast differentiation in a dose-dependent manner and achieved the best effect at 10 μmol·L-1 (P<0.01). Compared with the sRANKL group, different concentrations of TBⅡ down-regulated the mRNA levels of osteoclast differentiation-related genes c-Fos, RANK, and RANKL (P<0.05). None of 10 μmol·L-1 TBⅡ, 10 μmol·L-1 TBⅡ+10-4 μmol·L-1 ICA, or 10 μmol·L-1 TBⅡ+10-3 μmol·L-1 ICA affected the viability of RAW264.7 cells. TBⅡ and/or ICA inhibited osteoclast differentiation (P<0.01), and TBⅡ + ICA had the best effect (P<0.01). Compared with the sRANKL group, TBⅡ and/or ICA down-regulated the mRNA levels of c-Fos, RANK, and RANKL (P<0.05). The single application of TBⅡ and ICA had no significant effect on the mRNA levels of Wnt10b, Cthrc1, and C3a, while TBⅡ+ICA exerted up-regulating effects (P<0.05). Compared with those in the blank group, the bone differentiation and mineralization abilities of the normal osteogenic induction group and each osteogenic induction + osteoclast supernatant group were improved (P<0.01). Compared with the blank group, the normal osteogenic induction group and the osteogenic induction + osteoclast supernatant group showed up-regulated mRNA levels of Runx2 and OCN (P<0.01). ConclusionTBⅡ+ICA can inhibit osteoclast differentiation, maintain the normal osteoclast-osteoblast coupling, and promote osteogenic differentiation.
3.Associations of systemic immune-inflammation index and systemic inflammation response index with maternal gestational diabetes mellitus: Evidence from a prospective birth cohort study.
Shuanghua XIE ; Enjie ZHANG ; Shen GAO ; Shaofei SU ; Jianhui LIU ; Yue ZHANG ; Yingyi LUAN ; Kaikun HUANG ; Minhui HU ; Xueran WANG ; Hao XING ; Ruixia LIU ; Wentao YUE ; Chenghong YIN
Chinese Medical Journal 2025;138(6):729-737
BACKGROUND:
The role of inflammation in the development of gestational diabetes mellitus (GDM) has recently become a focus of research. The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI), novel indices, reflect the body's chronic immune-inflammatory state. This study aimed to investigate the associations between the SII or SIRI and GDM.
METHODS:
A prospective birth cohort study was conducted at Beijing Obstetrics and Gynecology Hospital from February 2018 to December 2020, recruiting participants in their first trimester of pregnancy. Baseline SII and SIRI values were derived from routine clinical blood results, calculated as follows: SII = neutrophil (Neut) count × platelet (PLT) count/lymphocyte (Lymph) count, SIRI = Neut count × monocyte (Mono) count/Lymph count, with participants being grouped by quartiles of their SII or SIRI values. Participants were followed up for GDM with a 75-g, 2-h oral glucose tolerance test (OGTT) at 24-28 weeks of gestation using the glucose thresholds of the International Association of Diabetes and Pregnancy Study Groups (IADPSG). Logistic regression was used to analyze the odds ratios (ORs) (95% confidence intervals [CIs]) for the the associations between SII, SIRI, and the risk of GDM.
RESULTS:
Among the 28,124 women included in the study, the average age was 31.8 ± 3.8 years, and 15.76% (4432/28,124) developed GDM. Higher SII and SIRI quartiles were correlated with increased GDM rates, with rates ranging from 12.26% (862/7031) in the lowest quartile to 20.10% (1413/7031) in the highest quartile for the SII ( Ptrend <0.001) and 11.92-19.31% for the SIRI ( Ptrend <0.001). The ORs (95% CIs) of the second, third, and fourth SII quartiles were 1.09 (0.98-1.21), 1.21 (1.09-1.34), and 1.39 (1.26-1.54), respectively. The SIRI findings paralleled the SII outcomes. For the second through fourth quartiles, the ORs (95% CIs) were 1.24 (1.12-1.38), 1.41 (1.27-1.57), and 1.64 (1.48-1.82), respectively. These associations were maintained in subgroup and sensitivity analyses.
CONCLUSION
The SII and SIRI are potential independent risk factors contributing to the onset of GDM.
Humans
;
Female
;
Pregnancy
;
Diabetes, Gestational/immunology*
;
Prospective Studies
;
Adult
;
Inflammation/immunology*
;
Glucose Tolerance Test
;
Birth Cohort
4.Establishment of a Bortezomib-Resistant Multiple Myeloma Xenotransplantation Mouse Model by Transplanting Primary Cells from Patients.
Yan-Hua YUE ; Yi-Fang ZHOU ; Ying-Jie MIAO ; Yang CAO ; Fei WANG ; Yue LIU ; Feng LI ; Yang-Ling SHEN ; Yan-Ting GUO ; Yu-Hui HUANG ; Wei-Ying GU
Journal of Experimental Hematology 2025;33(1):133-141
OBJECTIVE:
To explore the construction method of a resistant multiple myeloma (MM) patient-derived xenotransplantation (PDX) model.
METHODS:
1.0×107 MM patient-derived mononuclear cells (MNCs), 2.0×106 MM.1S cells and 2.0×106 NCI-H929 cells were respectively subcutaneously inoculated into NOD.CB17-Prkdcscid Il2rgtm1/Bcgen (B-NDG) mice with a volume of 100 μl per mouse to establish mouse model. The morphologic, phenotypic, proliferative and genetic characteristics of PDX tumor were studied by hematoxylin-eosin staining, immunohistochemical staining (IHC), cell cycle analysis, flow cytometry and fluorescence in situ hybridization (FISH). The sensitivity of PDX tumor to bortezomib and anlotinib monotherapy or in combination was investigated through cell proliferation, apoptosis and in vitro and in vivo experiments. The effects of anlotinib therapy on tumor blood vessel and cell apoptosis were analyzed by IHC, TUNEL staining and confocal fluorescence microscope.
RESULTS:
MM PDX model was successfully established by subcutaneously inoculating primary MNCs. The morphologic features of tumor cells from MM PDX model were similar to those of mature plasma cells. MM PDX tumor cells positively expressed CD138 and CD38, which presented 1q21 amplification, deletion of Rb1 and IgH rearrangement, and had a lower proliferative activity than MM cell lines. in vitro, PDX, MM.1S and NCI-H929 cells were treated by bortezomib and anlotinib for 24 hours, respectively. Cell viability assay showed that the IC50 value of bortezomib were 5 716.486, 1.025 and 2.775 nmol/L, and IC50 value of anlotinib were 5 5107.337, 0.706 and 5.13 μmol/L, respectively. Anlotinib treatment increased the apoptosis of MM.1S cells (P < 0.01), but did not affect PDX tumor cells (P >0.05). in vivo, there was no significant difference in PDX tumor growth between bortezomib monotherapy group and control group (P >0.05), while both anlotinib monotherapy and anlotinib combined with bortezomib effectively inhibited PDX tumor growth (both P < 0.05). The vascular perfusion and vascular density of PDX tumor were decreased in anlotinib treatment group (both P < 0.01). The apoptotic cells in anlotinib treatment group were increased compared with those in control group (P < 0.05).
CONCLUSION
Bortezomib-resistant MM PDX model can be successfully established by subcutaneous inoculation of MNCs from MM patients in B-NDG mice. This PDX model, which retains the basic biological characteristics of MM cells, can be used to study the novel therapies.
Animals
;
Bortezomib
;
Humans
;
Multiple Myeloma/pathology*
;
Mice
;
Apoptosis
;
Drug Resistance, Neoplasm
;
Cell Line, Tumor
;
Xenograft Model Antitumor Assays
;
Mice, Inbred NOD
;
Disease Models, Animal
;
Cell Proliferation
;
Transplantation, Heterologous
5.Association between Fish Consumption and Stroke Incidence Across Different Predicted Risk Populations: A Prospective Cohort Study from China.
Hong Yue HU ; Fang Chao LIU ; Ke Yong HUANG ; Chong SHEN ; Jian LIAO ; Jian Xin LI ; Chen Xi YUAN ; Ying LI ; Xue Li YANG ; Ji Chun CHEN ; Jie CAO ; Shu Feng CHEN ; Dong Sheng HU ; Jian Feng HUANG ; Xiang Feng LU ; Dong Feng GU
Biomedical and Environmental Sciences 2025;38(1):15-26
OBJECTIVE:
The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks.
METHODS:
A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI).
RESULTS:
During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43).
CONCLUSION
Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans
;
China/epidemiology*
;
Male
;
Female
;
Stroke/etiology*
;
Middle Aged
;
Prospective Studies
;
Incidence
;
Aged
;
Animals
;
Fishes
;
Risk Factors
;
Diet
;
Seafood
;
Adult
;
Cohort Studies
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