1.Finite element analysis of various root shield thicknesses in maxillary central incisor socket-shield technique
Guangneng CHEN ; Siyang LUO ; Mei WANG ; Bin YE ; Jiawen CHEN ; Yin LIU ; Yuwen ZUO ; Xianyu HE ; Jiajin SHEN ; Minxian MA
Chinese Journal of Tissue Engineering Research 2025;29(10):2052-2060
BACKGROUND:Socket-shield technique can effectively maintain labial soft and hard tissues,but the incidence of postoperative complications such as exposure and displacement of root shield is relatively high.It is speculated that the root shield may be exposed and displaced due to excessive load after long-term function of dental implants. OBJECTIVE:Through three-dimensional finite element analysis,we aim to study the influence of varying root shield thicknesses on the stress distribution,equivalent stress peaks,and displacement in the root shield,periodontal ligaments,implant,and surrounding alveolar bone under normal occlusal loading.We also attempt to analyze the correlation between the thickness of the root shield and occurrence of mechanical events such as root shield exposure,displacement,and fracture. METHODS:Cone-beam CT data of a patient who met the indication standard of socket-shield technique for maxillary central incisor were retrieved from database.Reverse engineering techniques were used to build models of the maxillary bone and root shield,while forward engineering was used to create models for the implant components based on their parameters.Models depicting various root shield thicknesses(0.5,1.0,1.5,and 2.0 mm)were created using Solidworks 2022 software.ANSYS Workbench 2021 software was then used to simulate and analyze the effects of varying root shield thicknesses on stress distribution,equivalent stress peaks,and displacement of the root shields,periodontal ligaments,implants,and surrounding alveolar bone under normal occlusion. RESULTS AND CONCLUSION:(1)In all root shield models,the stress was concentrated on the palatal cervical side,both sides of the edges and the lower edge of the labial side.As the thickness of the root shield increased,the equivalent stress peak and displacement showed a decreasing trend.The 0.5 mm thickness model produced a stress concentration of 176.20 MPa,which exceeded the yield strength(150 MPa)of tooth tissue.(2)The periodontal ligament stress in each group was concentrated in the neck margin and upper region.With the increase of root shield thickness,the equivalent stress peak and displacement of periodontal ligament showed a decreasing trend.(3)Implant stress in all models was concentrated in the neck of the implant and the joint of the implant-repair abutment,and the labial side was more concentrated than the palatal side.With the increase of root shield thickness,the equivalent stress peak of the implant in the model showed an increasing trend.(4)In each group of models,stress of cortical bone concentrated around the neck of the implant and the periphery of the root shield,and the labial side was more concentrated than the palatal side.With the increase of the thickness of the root shield,the equivalent stress peak around the root shield decreased;the peak value of the equivalent stress of the bone around the neck of the implant showed an increasing trend.In the model,the stress of cancellous bone was mainly concentrated around the neck of the lip of the implant,the top of the thread,the root tip and the lower margin of the root shield,and the labial side was more concentrated than the palatal side.With the increase of the thickness of the root shield,the peak value of the equivalent stress of the bone around the root shield in the model showed a decreasing trend.The minimum principal stress of cortical bone in each group of models was concentrated around the neck of the implant,exhibiting a fan-shaped distribution.As the thickness of the root shield increased,the minimum principal stress of cortical bone showed an increasing trend.(5)These results indicate that different thicknesses of the root shield have different biomechanical effects.The root shield with a thickness of 0.5 mm is easy to fracture.For patients with sufficient bone width,the root shield with a thickness of 2.0 mm is an option to reduce the risk of complications such as root shield exposure,fracture,and displacement.Meanwhile,it should be taken into account to protect the periodontal ligament in the preparation process,and rounding treatments ought to be carried out on both sides and the lower edge of the root shield.
2.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.
3.Working practices in eliminating the public health crisis caused by viral hepatitis in Hainan Province of China
Weihua LI ; Changfu XIONG ; Taifan CHEN ; Bin HE ; Dapeng YIN ; Xuexia ZENG ; Feng LIN ; Biyu CHEN ; Xiaomei ZENG ; Biao WU ; Juan JIANG ; Lu ZHONG ; Yuhui ZHANG
Journal of Clinical Hepatology 2025;41(2):228-233
In 2022, Hainan provincial government launched the project for the prevention and control of viral hepatitis with the goals of a hepatitis B screening rate of 90%, a diagnostic rate of 90%, and a treatment rate of 80% among people aged 18 years and above by the year 2025, and the main intervention measures include population-based prevention, case screening, antiviral therapy, and health management. As of December 31, 2024, a total of 6.875 million individuals in the general population had been screened for hepatitis B, with a screening rate of 95.6%. A total of 184 710 individuals with positive HBsAg were identified, among whom 156 772 were diagnosed through serological reexamination, resulting in a diagnostic rate of 84.9%. A total of 50 742 patients with chronic hepatitis B were identified, among whom 42 921 had hepatitis B-specific health records established for health management, with a file establishment rate of 84.6%. A total of 31 553 individuals received antiviral therapy, with a treatment rate of 62.2%. A total of 2.503 million individuals at a high risk of hepatitis C were screened, among whom 4 870 tested positive for HCV antibody and 3 858 underwent HCV RNA testing, resulting in a diagnostic rate of 79.2%, and 1 824 individuals with positive HCV RNA were identified, among whom 1 194 received antiviral therapy, with a treatment rate of 65.5%. In addition, 159 301 individuals with negative HBsAg and anti-HBs and an age of 20 — 40 years were inoculated with hepatitis B vaccine free of charge. Through the implementation of the project for the prevention and control of viral hepatitis, a large number of hepatitis patients have been identified, treated, and managed in the province within a short period of time, which significantly accelerates the efforts to eliminate the crisis of viral hepatitis.
4.Curcumin attenuates calcium oxalate crystal-induced renal injury via regulation of TLR4/NF-κB and NRF2/HO-1 pathways in mouse model
Yan-Feng HE ; Wen-Bin LAI ; Wen-Wei CHEN ; Chang-Yi LIU ; Kai-Xin LU ; Hua ZHANG ; Tao JIANG ; Rui GAO
Chinese Pharmacological Bulletin 2024;40(9):1701-1708
Aim To investigate the protective effects of curcumin(CUR)on crystal-induced renal injury and its underlying mechanism in the mouse model of neph-rolithiasis.Methods The mouse model of stone for-mation was established via successive intraperitoneal injection of glyoxylate.Proximal tubular epithelial cell line HK-2 treated with calcium oxalate monohydrate(COM)was used as an in vitro model.The protective role of CUR on nephrolithiasis was tested by determina-tion of tubular injury,crystal deposition and adhesion,levels of inflammatory cytokines.In vitro,the effects of CUR on the cell viability and inflammatory factors of HK-2 cells were measured.The proteins in the Toll-like receptor 4(TLR4)/nuclear factor κB(NF-κB)and nuclear factor erythroid 2-related factor 2(NRF2)/hemeoxygenase-1(HO-1)signaling path-ways were measured by Western blot for confirming the relationship between CUR and these pathways.Final-ly,NRF2 inhibitor ML385 and TLR4 activator CCL-34 were respectively used on COM-induced HK-2 cells ex-posed to CUR for the conduction of gain-of-function and loss-of-function assays.Results CUR improves the damage in the mouse model of kidney stone forma-tion,inhibits inflammation and antioxidative effects;promotes the viability of HK-2 cells induced by COM,and inhibits the expression of inflammatory factors.CUR suppresses the expression of proteins in the TLR4/NF-κB pathway,promotes the transfer of NRF2 from the cytoplasm to the nucleus,and enhances the ex-pression of HO-1.ML385 and CCL-34 respectively counteract the anti-inflammatory effects of CUR on COM-induced HK-2 cells.Conclusions Taken togeth-er,our study demonstrates the protective effect of CUR on the deposition of kidney stone and consequent tubu-lar injury.CUR through regulation of the TLR4/NF-κB and NRF2/HO-1 pathways improves renal injury.
5.Hydrogen sulfide and neuroinflammation-mediated neurodegenerative diseases
Yu-Lian SHUI ; Zhi-Qiong REN ; Yi-Jie HE ; Bin-Bin CHEN ; Jia HONG ; Ke-Ting LIU ; Li XIAO
Journal of Regional Anatomy and Operative Surgery 2024;33(6):551-554
Hydrogen sulfide,as a third gas signal molecule and neurotransmitter,can play a neuroprotective role by anti-oxidative stress,anti-inflammatory response,metabolic inhibition and other mechanisms.It is of great significance for the occurrence and development of neurodegenerative diseases including Alzheimer's disease(AD)and Parkinson's disease(PD)mediated by neuroinflammation.This article reviews the research progress of hydrogen sulfide and neuroinflammation and its mediated neurodegenerative diseases,so as to provide new ideas for the treatment of neurodegenerative diseases.
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.

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