1.Predictive value of preoperative inflammatory response indicators for incisional infection after spinal surgery.
Wei LIANG ; Rui-Li ZHUO ; Shao-Dong SUN
China Journal of Orthopaedics and Traumatology 2025;38(2):183-187
OBJECTIVE:
To explore the clinical significance of preoperative neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and C-reactive protein (CRP) to albumin (ALB) ratio in spinal surgery patients with postoperative incision infection.
METHODS:
A total of 373 patients who underwent spinal surgery were collected and devided into two groups according to the postoperative incision infection situation. Among them, 65 cases in the incision infection group included 34 males and 31 females with a mean age of (56.01±9.78) years old;308 cases in the non incision infection group included 157 males and 151 females with a mean age of (55.54±10.19) years old. Blood cell analyzer was applied to detect neutrophils, lymphocytes, and platelets, and calculate NLR and PLR;immunoturbidimetry was applied to measure serum CRP and ALB levels and calculate CRP/ALB ratio;receiver operating characteristic (ROC) curve was applied to analyze the predictive value of preoperative NLR, PLR, and CRP/ALB ratio for postoperative spinal incision infection;Logistic multivariate regression was applied to analyze the influencing factors of incision infection after spinal surgery.
RESULTS:
The NLR(4.92±1.13), PLR (119.32±22.74), CRP/ALB ratio (10.19±2.51), operation time (3.02±0.64) h, history of diabetes 38.46%(25/65), and the proportion of patients with implant 32.31%(21/65) in the incision infection group were higher than those in the non incision infection group 3.72±0.81, 90.58±20.16, 7.23±2.21, (2.26±0.51) h, 16.88%(53/308), 11.69%(36/308), there were statistical differences(P<0.05). The AUC of preoperative NLR, PLR, and CRP/ALB ratio alone and in combination for predicting postoperative incision infection after spinal surgery was 0.786, 0.806, 0.839, and 0.926, respectively. Preoperative NLR, PLR, and CRP/ALB ratio were independent risk factors for postoperative incision infection in spinal surgery(P<0.05).
CONCLUSION
The determination of preoperative NLR, PLR, and CRP/ALB ratio is beneficial for early prediction of postoperative spinal incision infection, and the combined detection of the three can further improve the accuracy of the prediction results.
Humans
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Male
;
Female
;
Middle Aged
;
Aged
;
C-Reactive Protein/metabolism*
;
Surgical Wound Infection/etiology*
;
Adult
;
Spine/surgery*
;
Inflammation
;
Preoperative Period
2.Comparison of application and efficacy of domestic HURWA and imported Smith & Nephew Cori robots in total knee arthroplasty.
Ming-You WANG ; Zhuo-Dong TANG ; Yu-Ping LAN ; Heng XIAO ; Ming-Li WANG ; Xun-Zhou SONG ; Hong-Ping WANG
China Journal of Orthopaedics and Traumatology 2025;38(10):1027-1036
OBJECTIVE:
Investigation on the clinical application of HURWA robot and Smith & Nephew Cori robot in total knee arthroplasty(TKA).
METHODS:
A retrospective analysis was performed on 84 patients with knee osteoarthritis who underwent robotic-assisted TKA (RATKA) between June 2023 and March 2025. According to the different robotic systems used, the patients were divided into the domestic HUARUN robotic-assisted total knee arthroplasty group (HRATKA group) and the Smith & Nephew Cori robotic-assisted total knee arthroplasty group (CRATKA group). There were 42 patients in the HRATKA group, including 16 males and 26 females; the age ranged from 56 to 73 years old, with an average of (64.70±8.30) years old;the body mass index (BMI) was (25.10±2.30) kg·m-2;21 cases were on the right side and 21 cases on the left side;in terms of Kellgren-Lawrence(K-L) classification, there were 15 cases of Grade Ⅲ and 27 cases of Grade Ⅳ;the disease duration ranged from 3 to 25 years, with an average of (15.5±7.5) years. The CRATKA group also included 42 patients, with 14 males and 28 females;the age ranged from 58 to 74 years old, with an average of (65.60±7.50) years old;the BMI was (24.50±2.70) kg·m-2; 20 cases were on the right side and 22 cases on the left side;regarding K-L classification, there were 11 cases of Grade Ⅲ and 31 cases of Grade Ⅳ;the disease duration ranged from 2 to 26 years, with an average of (16.5±8.8) years. Collect general data of all patients, including age, gender, height, weight, surgical site, K-L classification, incision length, and operation time. To evaluate prosthesis position, compare the frontal tibia component (FTC) angle, lateral femoral component (LFC) angle, lateral tibia component (LTC) angle, and frontal femoral component angle between the two groups of patients after surgery. Measure the deviation of the hip-knee-ankle (HKA) angle to assess lower limb alignment. Additionally, compare the following indicators between the two groups:Knee Society Score (KSS), Visual Analogue Scale (VAS) for pain, knee range of motion (ROM), hemoglobin (HB) level, hematocrit (HCT) level, complication rate, and in-hospital satisfaction.
RESULTS:
All patients successfully completed the surgery as scheduled, and all were followed up after the operation. The follow-up period ranged from 5 to 17 months with an average of (11.2±6.1) months. There were 4 cases of venous thrombosis in the HRATKA group and 3 cases in the CRATKA group;each group had 2 cases of wound exudation. No mechanical-related complications, pulmonary embolism, or other severe complications occurred. Comparison of the incision length and hospital stay between the HRATKA group and the CRATKA group showed no statistically significant difference (P>0.05). The operation time in the HRATKA group was (96.80±7.10) minutes, which was longer than that in the CRATKA group (90.10±8.80) minutes, and the difference was statistically significant (P<0.05). In the HRATKA group, the HKA angle was (178.93±1.11) degree, the FFC angle was (89.00±0.91)°, and the LFC angle was (7.31±2.17) degree;the corresponding values in the CRATKA group were (178.05±1.34)°, (87.88±1.74)°, and (10.60±2.84) degree respectively. The differences in these three indicators between the two groups were all statistically significant (P<0.05). However, there were no statistically significant differences in the FTC angle or LTC angle between the two groups (P>0.05). There was also no statistically significant difference in the total perioperative blood loss between the two groups (P>0.05). At 3 days after surgery, the VAS score for movement in the HRATKA group (5.95±1.45) points was higher than that in the CRATKA group (4.50±0.97) points, with a statistically significant difference (P<0.05);at 90 days after surgery, there was no statistically significant difference in the movement VAS score between the two groups (P>0.05). Additionally, no statistically significant differences were observed between the two groups in the KSS, ROM at 3 and 90 days after surgery, or satisfaction degree during hospitalization (all P>0.05).
CONCLUSION
The domestic HURWA robot demonstrates excellent performance in osteotomy efficiency and lower limb alignment recovery. The Smith & Nephew Cori robot has a significant advantage in soft tissue assessment and joint stability optimization. Both robotic systems offer high-quality surgical treatments that significantly improve short-term knee function.
Humans
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Male
;
Female
;
Arthroplasty, Replacement, Knee/instrumentation*
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Aged
;
Middle Aged
;
Retrospective Studies
;
Robotic Surgical Procedures/methods*
;
Osteoarthritis, Knee/surgery*
3.Network pharmacology analysis based on potential mechanism of dandelion-mulberry leaf in treatment of acute myeloid leukemia
Xinchen ZHOU ; Shuhan DONG ; Zhuo ZHANG ; Mingmei SHEN ; Xiangjun WANG ; Ying LI ; Limei LIU
Journal of Jilin University(Medicine Edition) 2024;50(4):1087-1097
Objective:To analyze the role of dandelion and mulberry leaf in the progression of acute myeloid leukemia(AML)by network pharmacology,and to clarify the active components and their mechanisms in treating AML.Methods:The active components of dandelion and mulberry leaf were screened by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP).The targets were predicted by SwissTargetPrediction Database.The AML-related genes and protein targets were retrieved from the SymMap Database,the GeneCards Human Gene Database,the DisGeNET Database,and the Online Mendelian Inheritance in Man(OMIM)Database.The AML-related genes and target genes of dandelion and mulberry leaf were compared by comparative analysis and were identify by the enrichment genes,followed by Gene Ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analysis.The drug-active component-target network and protein-protein interaction(PPI)network were constructed by Cytoscape 3.8.0 software,and the core genes were selected by CytoNCA plugin;the molecular docking was conducted by AutoDock software.Results:After filtering by databases,39 active components were identified,and 148 common targets between dandelion-mulberry leaf and AML were collected.The GO functional enrichment analysis mainly involved cytokine-mediated signaling pathways,positive regulation of kinase activity,and oxidative stress responses.The KEGG signaling pathway enrichment analysis focused on the phosphatidylinositol 3 kinase/protein kinase B(PI3K-AKT)signaling pathway,the tumor necrosis factor(TNF)signaling pathway,and the Janus kinase/signal transducer and activator of transcription(JAK-STAT)signaling pathway.The key targets were identified by topological analysis including signal transducer and activator of transcription 3(STAT3),epidermal growth factor receptor(EGFR),protein kinase B1(AKT1),recombinant human epidermal growth factor(EGF),vascular endothelial growth factor A(VEGFA),oncogene MYC,tumor protein P53(TP53),mitogen-activated protein kinase 3(MAPK3),cysteiny asparate specific protease-3(CASP3),oncogene SRC,heat shock protein 90 alpha family class A member 1(HSP90AA1),tenascin XB1(CTNNB1),phosphoinositide kinase-3 catalytic subunit alpha(PIK3CA),interleukin 6(IL-6),TNF,mitogen-activated protein kinase 1(MAPK1),and phosphatidylinositide kinase-3 regulatory subunit 1(PIK3R1).The molecular docking results showed the highest affinity pairing to be taraxerol with MYC(-8.74 kcal·mol-1),and quercetin,kaempferol,luteolin,and artemetin demonstrated good binding affinities with various targets.Conclusion:The main active components of dandelion-mulberry leaf,such as quercetin,taraxerol,kaempferol,luteolin,and artemetin,may exert the anti-AML effect by regulating AKT1,STAT3,HSP90AA1,IL-6,and MAPK1;regulation the PI3K-AKT signaling pathway may be the critical mechanism of anti-AML effect by dandelion-mulberry leaf.
4.3D printed Mg-incorporated polycaprolactone scaffolds for repairing rat skull defects
LI Xiaoye ; LI Qiang ; DAI Zhuo ; DING Meng ; DONG Heng ; DONG Qiangsheng ; BAI Jing ; MOU Yongbin
Journal of Prevention and Treatment for Stomatological Diseases 2024;32(4):249-256
Objective:
To evaluate the bone repair effect of 3D-printed magnesium (Mg)-loaded polycaprolactone (PCL) scaffolds in a rat skull defect model.
Methods:
PCL scaffolds mixed with Mg microparticles were prepared by using 3D printing technology, as were pure PCL scaffolds. The surface morphologies of the two scaffolds were observed by scanning electron microscopy (SEM), and the surface elemental composition was analyzed via energy dispersive spectroscopy (EDS). The physical properties of the scaffolds were characterized through contact angle measurements and an electronic universal testing machine. This study has been reviewed and approved by the Ethics Committee. A critical size defect model was established in the skull of 15 Sprague-Dawley (SD) rats, which were divided into the PCL group, PCL-Mg group, and untreated group, with 5 rats in each group. Micro-CT scanning was performed to detect and analyze skull defect healing at 4 and 8 weeks after surgery, and samples from the skull defect area and major organs of the rats were obtained for histological staining at 8 weeks after surgery.
Results:
The scaffolds had a pore size of (480 ± 25) μm, a fiber diameter of (300 ± 25) μm, and a porosity of approximately 66%. The PCL-Mg scaffolds contained 1.0 At% Mg, indicating successful incorporation of Mg microparticles. The contact angle of the PCL-Mg scaffolds was 68.97° ± 1.39°, indicating improved wettability compared to that of pure PCL scaffolds. Additionally, compared with that of pure PCL scaffolds, the compressive modulus of the PCL-Mg scaffolds was (57.37 ± 8.33) MPa, demonstrating enhanced strength. The PCL-Mg group exhibited the best bone formation behavior in the skull defect area compared with the control group and PCL group at 4 and 8 weeks after surgery. Moreover, quantitative parameters, such as bone volume (BV), bone volume/total volume (BV/TV), bone surface (BS), bone surface/total volume (BS/TV), trabecular thickness (Tb.Th), trabecular number (Tb.N) and bone mineral density (BMD), of skull defects were better than those in the other groups, indicating the best bone regeneration effect. H&E, Goldner, and VG staining revealed more mineralized new bone formation in the PCL-Mg group than in the other groups, and H&E staining of the major organs revealed good biosafety of the material.
Conclusion
PCL-Mg scaffolds can promote the repair of bone defects and have clinical potential as a new scaffold material for the repair of maxillofacial bone defects.
5.National bloodstream infection bacterial resistance surveillance report (2022) : Gram-negative bacteria
Zhiying LIU ; Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Haifeng MAO ; Hui DING ; Pengpeng TIAN ; Jiangqin SONG ; Yongyun LIU ; Jiliang WANG ; Yan JIN ; Yuanyuan DAI ; Yizheng ZHOU ; Yan GENG ; Fenghong CHEN ; Lu WANG ; Yanyan LI ; Dan LIU ; Peng ZHANG ; Junmin CAO ; Xiaoyan LI ; Dijing SONG ; Xinhua QIANG ; Yanhong LI ; Qiuying ZHANG ; Guolin LIAO ; Ying HUANG ; Baohua ZHANG ; Liang GUO ; Aiyun LI ; Haiquan KANG ; Donghong HUANG ; Sijin MAN ; Zhuo LI ; Youdong YIN ; Kunpeng LIANG ; Haixin DONG ; Donghua LIU ; Hongyun XU ; Yinqiao DONG ; Rong XU ; Lin ZHENG ; Shuyan HU ; Jian LI ; Qiang LIU ; Liang LUAN ; Jilu SHEN ; Lixia ZHANG ; Bo QUAN ; Xiaoping YAN ; Xiaoyan QI ; Dengyan QIAO ; Weiping LIU ; Xiusan XIA ; Ling MENG ; Jinhua LIANG ; Ping SHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2024;17(1):42-57
Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System(BRICS)were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period,9 035 strains of Gram-negative bacteria were collected from 51 hospitals,of which 7 895(87.4%)were Enterobacteriaceae and 1 140(12.6%)were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli( n=4 510,49.9%), Klebsiella pneumoniae( n=2 340,25.9%), Pseudomonas aeruginosa( n=534,5.9%), Acinetobacter baumannii complex( n=405,4.5%)and Enterobacter cloacae( n=327,3.6%). The ESBLs-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus spp. were 47.1%(2 095/4 452),21.0%(427/2 033)and 41.1%(58/141),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(58/4 510)and 13.1%(307/2 340);62.1%(36/58)and 9.8%(30/307)of CREC and CRKP were resistant to ceftazidime/avibactam combination,respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 59.5%(241/405),while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 18.4%(98/534). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions,with statistically significant differences in the prevalence of CRKP and CRPA( χ2=20.489 and 20.252, P<0.001). The prevalence of CREC,CRKP,CRPA,CRAB,ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals( χ2=11.953,81.183,10.404,5.915,12.415 and 6.459, P<0.01 or <0.05),while the prevalence of CRPA was higher in economically developed regions(per capita GDP ≥ 92 059 Yuan)than that in economically less-developed regions(per capita GDP <92 059 Yuan)( χ2=6.240, P=0.012). Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend,and Escherichia coli is ranked in the top,while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different,and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.
6.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.
7.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.
8.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.
9.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.
10.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.


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