1.The risk prediction models for anastomotic leakage after esophagectomy: A systematic review and meta-analysis
Yushuang SU ; Yan LI ; Hong GAO ; Zaichun PU ; Juan CHEN ; Mengting LIU ; Yaxie HE ; Bin HE ; Qin YANG
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2025;32(02):230-236
Objective To systematically evaluate the risk prediction models for anastomotic leakage (AL) in patients with esophageal cancer after surgery. Methods A computer-based search of PubMed, EMbase, Web of Science, Cochrane Library, Chinese Medical Journal Full-text Database, VIP, Wanfang, SinoMed and CNKI was conducted to collect studies on postoperative AL risk prediction model for esophageal cancer from their inception to October 1st, 2023. PROBAST tool was employed to evaluate the bias risk and applicability of the model, and Stata 15 software was utilized for meta-analysis. Results A total of 19 literatures were included covering 25 AL risk prediction models and 7373 patients. The area under the receiver operating characteristic curve (AUC) was 0.670-0.960. Among them, 23 prediction models had a good prediction performance (AUC>0.7); 13 models were tested for calibration of the model; 1 model was externally validated, and 10 models were internally validated. Meta-analysis showed that hypoproteinemia (OR=9.362), postoperative pulmonary complications (OR=7.427), poor incision healing (OR=5.330), anastomosis type (OR=2.965), preoperative history of thoracoabdominal surgery (OR=3.181), preoperative diabetes mellitus (OR=2.445), preoperative cardiovascular disease (OR=3.260), preoperative neoadjuvant therapy (OR=2.977), preoperative respiratory disease (OR=4.744), surgery method (OR=4.312), American Society of Anesthesiologists score (OR=2.424) were predictors for AL after esophageal cancer surgery. Conclusion At present, the prediction model of AL risk in patients with esophageal cancer after surgery is in the development stage, and the overall research quality needs to be improved.
2.Differential component analysis between Fructus Tritici Levis and Triticum aestivum based on qualitative and quantitative methods
Xuejiao LI ; Yu HU ; Yun CHEN ; Juan SHANG ; Zhenyang LI ; Yunhua FENG ; Jiandong ZOU ; Weifeng YAO ; Su LU ; Meijuan XU
China Pharmacy 2024;35(11):1296-1302
OBJECTIVE To analyze the compositional differences between Fructus Tritici Levis and Triticum aestivum, and to provide reference for identification and quality control of both. METHODS Twenty batches of Fructus Tritici Levis and three batches of T. aestivum were collected, and their fingerprints were acquired by high-performance liquid chromatography and the similarities were evaluated by the Evaluation System of Similarity of Chromatographic Fingerprints of Traditional Chinese Medicine (2012 version). Cluster analysis (CA), principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed to analyze the difference of Fructus Tritici Levis and T. aestivum from different regions, and the differential components were screened. The contents of the six identified components in Fructus Tritici Levis and T. aestivum were determined. RESULTS The similarities of the fingerprints of Fructus Tritici Levis ranged from 0.928 to 0.996, and the relative similarities of T. aestivum with Fructus Tritici Levis ranged from 0.761 to 0.773. A total of 19 common peaks were calibrated, and six components including linolenic acid, linoleic acid, 5-heptadecylresorcinol, 5-nonadodecylresorcinol, 5- heneicosylresorcinol, and 5-tricosylresorcinol were identified. The results of CA and PCA showed that Fructus Tritici Levis and T. aestivum could be clearly distinguished; the distribution of Fructus Tritici Levis from Anhui province was relatively concentrated. The results of OPLS-DA showed that linolenic acid, linoleic acid, and other six unknown compounds were the differential components between Fructus Tritici Levis and T. aestivum. The average contents of the six identified components in Fructus Tritici Levis were 0.100 9, 1.094 0, 0.005 1, 0.030 9, 0.098 2,and 0.024 8 mg/g, respectively; the contents of linolenic acid and linoleic acid in Fructus Tritici Levis were significantly higher than those in T. aestivum (P<0.05).CONCLUSIONS The established qualitative and quantitative methods are simple and reliable, and can be used for the identification and quality evaluation of Fructus Tritici Levis and T. aestivum. The identified differential components, such as linolenic acid and linoleic acid, can also provide clues for the differentiation and pharmacological study of Fructus Tritici Levis and T. aestivum.
3.Differential component analysis between Fructus Tritici Levis and Triticum aestivum based on qualitative and quantitative methods
Xuejiao LI ; Yu HU ; Yun CHEN ; Juan SHANG ; Zhenyang LI ; Yunhua FENG ; Jiandong ZOU ; Weifeng YAO ; Su LU ; Meijuan XU
China Pharmacy 2024;35(11):1296-1302
OBJECTIVE To analyze the compositional differences between Fructus Tritici Levis and Triticum aestivum, and to provide reference for identification and quality control of both. METHODS Twenty batches of Fructus Tritici Levis and three batches of T. aestivum were collected, and their fingerprints were acquired by high-performance liquid chromatography and the similarities were evaluated by the Evaluation System of Similarity of Chromatographic Fingerprints of Traditional Chinese Medicine (2012 version). Cluster analysis (CA), principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed to analyze the difference of Fructus Tritici Levis and T. aestivum from different regions, and the differential components were screened. The contents of the six identified components in Fructus Tritici Levis and T. aestivum were determined. RESULTS The similarities of the fingerprints of Fructus Tritici Levis ranged from 0.928 to 0.996, and the relative similarities of T. aestivum with Fructus Tritici Levis ranged from 0.761 to 0.773. A total of 19 common peaks were calibrated, and six components including linolenic acid, linoleic acid, 5-heptadecylresorcinol, 5-nonadodecylresorcinol, 5- heneicosylresorcinol, and 5-tricosylresorcinol were identified. The results of CA and PCA showed that Fructus Tritici Levis and T. aestivum could be clearly distinguished; the distribution of Fructus Tritici Levis from Anhui province was relatively concentrated. The results of OPLS-DA showed that linolenic acid, linoleic acid, and other six unknown compounds were the differential components between Fructus Tritici Levis and T. aestivum. The average contents of the six identified components in Fructus Tritici Levis were 0.100 9, 1.094 0, 0.005 1, 0.030 9, 0.098 2,and 0.024 8 mg/g, respectively; the contents of linolenic acid and linoleic acid in Fructus Tritici Levis were significantly higher than those in T. aestivum (P<0.05).CONCLUSIONS The established qualitative and quantitative methods are simple and reliable, and can be used for the identification and quality evaluation of Fructus Tritici Levis and T. aestivum. The identified differential components, such as linolenic acid and linoleic acid, can also provide clues for the differentiation and pharmacological study of Fructus Tritici Levis and T. aestivum.
4.Preparation and Performance Characterization of Microcapsules Containing Ethanol Extract from Galangal
Su-Juan PENG ; Zhen-Rong WEN ; Zhen-Ying FENG ; Dan CHEN ; Jian-Wen WANG ; Li-Ping HUANG
Journal of Guangzhou University of Traditional Chinese Medicine 2024;41(5):1307-1315
Objective To explore the best preparation process and performance characterization of microcapsules containing ethanol extract from galangal.Methods With gum arabic(GA)-chitosan(CS)as capsule wall material,microcapsules were prepared by complex coacervation method.With drug loading and encapsulation efficiency as indexes,the optimal preparation technology of microcapsules was screened by orthogonal design method.The content of ethanol extract of galangal in microcapsules was determined by high performance liquid chromatography(HPLC).The prepared microcapsules were characterized by infrared spectrometer and scanning electron microscope.Results The optimum preparation conditions of microcapsules containing galangal ethanol extract were as follows:wall material ratio(GA/CS)6∶1,core to wall ratio 1∶1,coagulation time 45 minutes,curing agent dosage 3 mL.Under these conditions,the drug loading and encapsulation efficiency of microcapsules containing galangal ethanol extract were 27.17%and 80.07%,respectively,and the sustained release performance of microcapsules of galangal ethanol extract was superior to that of galangal ethanol extract.Conclusion The preparation of microcapsules containing galangal ethanol extract by complex coacervation method has good encapsulation,and the method is simple,stable and reliable,and has high feasibility.
5.Clinical efficacy of Zhiyang Xiaozhen granules combined with second-generation antihistamine in the treatment of chronic urticaria
Li ZHANG ; Bo YANG ; Qiaozhi CAO ; Cong PENG ; Mingliang CHEN ; Juan SU ; Xiang CHEN ; Jie LI
Journal of Central South University(Medical Sciences) 2024;49(2):175-181
Objective:Chronic urticaria presents a chronic process of recurrent attacks,and its first-line treatment is second-generation antihistamine with limited treatment options.The efficacy of antihistamine varies among individuals and cannot meet the needs of all patients.This study aims to explore the clinical efficacy and safety of Zhiyang Xiaozhen granules combined with antihistamine in the treatment of chronic urticaria patients. Methods:We retrospectively analyzed the clinical data of patients with chronic urticaria who visited the Xiangya Hospital of Central South University from April 2020 to March 2021.The patients who received conventional second-generation antihistamine treatment were selected as a control group,while the patients who received combined treatment with Zhiyang Xiaozhen granules on the basis of conventional second-generation antihistamine treatment were selected as an observation group.The differences in the Weekly Urticaria Activity Score(UAS7)and Dermatology Life Quality Index(DLQI)between the 2 groups before and 4 weeks after treatment were compared.The Symptom Score Reduce Index(SSRI)was used to evaluate and compare the efficacy of the 2 treatment regimens. Results:After 4 weeks of treatment,the UAS7 levels in both groups were significantly reduced(P=0.001 and P<0.001,respectively).The effective rates of the control group and the observation group were 61.11%and 59.38%,respectively when converting UAS7 to SSRI for efficacy evaluation,and there was no statistically significant difference in efficacy between the 2 groups(P>0.05);however,when converting DLQI to SSRI for efficacy evaluation,the effective rates of the control group and the observation group were 33.33%and 46.88%,respectively,and the difference in efficacy between the 2 groups was statistically significant(P<0.001).There were 3 patients with adverse drug reactions related to drowsiness in both groups. Conclusion:The combination of Zhiyang Xiaozhen granules and second-generation antihistamine can effectively improve disease activity in patients with chronic urticaria,and the improvement in quality of life is better than that with the second-generation antihistamine alone.
6.Application of digital technology in the repair of functional and aesthetic defects in patients with acid erosion and severe attrition:a case report
Weiwei HOU ; Xuhong ZHENG ; Xiaoling CHEN ; Weiliang CAI ; Chaoyang WANG ; Zhiwei SU ; Juan ZHAO
West China Journal of Stomatology 2024;42(1):111-120
Noncarious lesions,a multifactorial condition encompassing tooth attrition,abrasion,and erosion,have a surge in prevalence and required increased attention in clinical practice.These nonbacterial-associated tooth de-fects can compromise aesthetics,phonetics,and mastica-tory functions.When providing full-arch fixed occlusal rehabilitation for such cases,the treatment strategy should extend beyond by restoring dentition morphology and aesthetics.This report details a complex case of erosive dental wear addressed through a fully digital,full-arch fixed occlusal rehabilitation.A 4D virtual patient was created using multiple digital data sources,including intraoral scanning,3D facial scanning,digital facebow registration,and mandibular movement tracing.With a comprehensive understanding of the masticatory system,various types of microinvasive prostheses were customized for each tooth,including labial ve-neers,buccal-occlusal veneers,occlusal veneers,overlays,inlays,and full crowns,were customized for each tooth.The reported digital workflow offered a predictable diagnostic and treatment strategy,which was facilitated by virtual visual-ization and comprehensive quality control throughout the process.
7.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.
8.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
9.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
10.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.

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