1.A Study of Flow Sorting Lymphocyte Subsets to Detect Epstein-Barr Virus Reactivation in Patients with Hematological Malignancies.
Hui-Ying LI ; Shen-Hao LIU ; Fang-Tong LIU ; Kai-Wen TAN ; Zi-Hao WANG ; Han-Yu CAO ; Si-Man HUANG ; Chao-Ling WAN ; Hai-Ping DAI ; Sheng-Li XUE ; Lian BAI
Journal of Experimental Hematology 2025;33(5):1468-1475
OBJECTIVE:
To analyze the Epstein-Barr virus (EBV) load in different lymphocyte subsets, as well as clinical characteristics and outcomes in patients with hematologic malignancies experiencing EBV reactivation.
METHODS:
Peripheral blood samples from patients were collected. B, T, and NK cells were isolated sorting with magnetic beads by flow cytometry. The EBV load in each subset was quantitated by real-time quantitative polymerase chain reaction (RT-qPCR). Clinical data were colleted from electronic medical records. Survival status was followed up through outpatient visits and telephone calls. Statistical analyses were performed using SPSS 25.0.
RESULTS:
A total of 39 patients with hematologic malignancies were included, among whom 35 patients had undergone allogeneic hematopoietic stem cell transplantation (allo-HSCT). The median time to EBV reactivation was 4.8 months (range: 1.7-57.1 months) after allo-HSCT. EBV was detected in B, T, and NK cells in 20 patients, in B and T cells in 11 patients, and only in B cells in 4 patients. In the 35 patients, the median EBV load in B cells was 2.19×104 copies/ml, significantly higher than that in T cells (4.00×103 copies/ml, P <0.01) and NK cells (2.85×102 copies/ml, P <0.01). Rituximab (RTX) was administered for 32 patients, resulting in EBV negativity in 32 patients with a median time of 8 days (range: 2-39 days). Post-treatment analysis of 13 patients showed EBV were all negative in B, T, and NK cells. In the four non-transplant patients, the median time to EBV reactivation was 35 days (range: 1-328 days) after diagnosis of the primary disease. EBV was detected in one or two subsets of B, T, or NK cells, but not simultaneously in all three subsets. These patients received a combination chemotherapy targeting at the primary disease, with 3 patients achieving EBV negativity, and the median time to be negative was 40 days (range: 13-75 days).
CONCLUSION
In hematologic malignancy patients after allo-HSCT, EBV reactivation commonly involves B, T, and NK cells, with a significantly higher viral load in B cells compared to T and NK cells. Rituximab is effective for EBV clearance. In non-transplant patients, EBV reactivation is restricted to one or two lymphocyte subsets, and clearance is slower, highlighting the need for prompt anti-tumor therapy.
Humans
;
Hematologic Neoplasms/virology*
;
Herpesvirus 4, Human/physiology*
;
Epstein-Barr Virus Infections
;
Hematopoietic Stem Cell Transplantation
;
Virus Activation
;
Lymphocyte Subsets/virology*
;
Flow Cytometry
;
Killer Cells, Natural/virology*
;
Male
;
Female
;
B-Lymphocytes/virology*
;
Viral Load
;
Adult
;
T-Lymphocytes/virology*
;
Middle Aged
2.Integrated Medicine Treatment of Rare Bone Marrow Tuberculosis in Systemic Lupus Erythematosus and Potentiating and Detoxifying Effects of Chinese Medicine: A Case Report.
Wu CHEN ; Lin HUANG ; Wei-Man SHI ; Ke MA ; Cheng-Ping WEN ; Qiao-Ding DAI
Chinese journal of integrative medicine 2025;31(2):153-156
3.National bloodstream infection bacterial resistance surveillance report 2023: Gram-positive bacteria
Chaoqun YING ; Jinru JI ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(2):118-132
Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System(BRICS)during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute(CLSI). Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus( n=1 544,35.2%),coagulase-negative Staphylococci( n=1 441,32.9%), Enterococcus faecium( n=574,13.1%), Enterococcus faecalis( n=385,8.8%),and α-hemolytic Streptococci( n=187,4.3%). The prevalence of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)was 26.2%(405/1 544)and 69.8%(1 006/1 441),respectively. Notably,all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility(>97.0%)to cephalobiol,rifampicin,trimethoprim-sulfamethoxazole,linezolid,minocycline,tigecycline,and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium(resistance to vancomycin and teicoplanin:both 1.7%)compared to Enterococcus faecalis(both 0.3%). The detection rates of MRSA and MRCNS exhibited significant regional variations across the country( χ2=17.674 and 148.650,respectively,both P<0.001). No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA( χ2=14.111, P<0.001)and MRCNS( χ2=4.828, P=0.028)in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA( χ2=18.986, P<0.001)and MRCNS( χ2=4.477, P=0.034)in less developed regions(per capita GDP
4.National bloodstream infection bacterial resistance surveillance report (2023) : Gram-negative bacteria
Jinru JI ; Zhiying LIU ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(1):47-62
Objective:To report the results of bacterial resistant investigation collaborative system(BRICS)on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023,and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. 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 were used to analyze the data.Results:During the study period,11 492 strains of Gram-negative bacteria were collected from 60 hospitals,of which 10 098(87.9%)were Enterobacterales and 1 394(12.1%)were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli(50.0%), Klebsiella pneumoniae(26.1%), Pseudomonas aeruginosa(5.1%), Acinetobacter baumannii complex(5.0%)and Enterobacter cloacae complex(4.1%). The ESBL-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus mirablilis were 46.8%(2 685/5 741),18.3%(549/2 999)and 44.0%(77/175),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(76/5 741)and 15.0%(450/2 999);32.9%(25/76)and 78.0%(351/450)of CREC and CRKP were sensitive to ceftazidime/avibactam combination,respectively. 94.7%(72/76)and 90.2%(406/450)of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore,57.9%(44/76)and 79.1%(356/450)were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 64.6%(370/573),while more than 80.0% of CRAB complex was sensitive to tigecycline,eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 17.0%(99/581). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China,with statistically significant differences in the prevalence of CREC,CRKP,CRPA and CRAB complex( χ2=10.6,28.6,10.8 and 19.3, P<0.05). The prevalence of ESBL-producing Escherichia coli, CREC,CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals( χ2=12.5,9.8,12.7 and 57.8,all P<0.01). Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China,and Escherichia coli is ranked in the top,while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend,CREC infecton maintains a low prevalence level,and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.
5.Mechanism of cordycepin in treatment of asthma based on network pharmacology and molecular docking technology
Man-ling JIANG ; Lei ZHANG ; Yao LIU ; Guo-ping LI ; Jin-wei HUANG
Chinese Pharmacological Bulletin 2025;41(11):2158-2166
Aim To explore the potential mechanisms underlying therapeutic effects of cordycepin in asthma by utilizing network pharmacology,molecular docking,and in vitro cellular validation.Methods The thera-peutic targets associated with asthma and the drug tar-gets of cordycepin were systematically identified through comprehensive database searches.An overlap analysis of the two gene sets was performed,followed by the construction of a protein-protein interaction(PPI)network and topological analysis to identify the core targets.The core targets were subjected to Kyoto Ency-clopedia of Genes and Genomes(KEGG)pathway a-nalysis and Gene Ontology(GO)enrichment analysis,and a drug-target-pathway network was constructed.To validate the interaction between cordycepin and core targets,molecular docking and molecular dynamics sim-ulations were conducted.Subsequently,the pharmaco-logical effects and underlying mechanisms of cordyce-pin were validated in vitro using Beas-2B cells,emplo-ying Cell Counting Kit-8(CCK-8)assay and quantita-tive real-time reverse transcription PCR(RT-qPCR).Results A total of 438 potential targets of cordycepin were identified,113 of which overlapped with asthma-related therapeutic targets.Topological analysis based on the PPI network revealed 22 core targets.Using KEGG enrichment analysis,165 significantly enriched pathways were identified,including the TNF and HIF-1 signaling pathways.Molecular docking analysis re-vealed high binding affinities between cordycepin and select core targets,which further corroborated by mo-lecular dynamics simulations.In vitro experiments showed that after cordycepin pretreatment,the upregu-lation of MAPK1,HIF1A,MTOR,MYC,IL10,and JUN mRNA was significantly rescued in HDM-stimulated Beas-2B cells.Conclusions Cordycepin exerts anti-asthmatic effects by targeting MAPK1 and other key molecules,thereby providing a scientific foundation for its further development and clinical application.
6.Mechanism of cordycepin in treatment of asthma based on network pharmacology and molecular docking technology
Man-ling JIANG ; Lei ZHANG ; Yao LIU ; Guo-ping LI ; Jin-wei HUANG
Chinese Pharmacological Bulletin 2025;41(11):2158-2166
Aim To explore the potential mechanisms underlying therapeutic effects of cordycepin in asthma by utilizing network pharmacology,molecular docking,and in vitro cellular validation.Methods The thera-peutic targets associated with asthma and the drug tar-gets of cordycepin were systematically identified through comprehensive database searches.An overlap analysis of the two gene sets was performed,followed by the construction of a protein-protein interaction(PPI)network and topological analysis to identify the core targets.The core targets were subjected to Kyoto Ency-clopedia of Genes and Genomes(KEGG)pathway a-nalysis and Gene Ontology(GO)enrichment analysis,and a drug-target-pathway network was constructed.To validate the interaction between cordycepin and core targets,molecular docking and molecular dynamics sim-ulations were conducted.Subsequently,the pharmaco-logical effects and underlying mechanisms of cordyce-pin were validated in vitro using Beas-2B cells,emplo-ying Cell Counting Kit-8(CCK-8)assay and quantita-tive real-time reverse transcription PCR(RT-qPCR).Results A total of 438 potential targets of cordycepin were identified,113 of which overlapped with asthma-related therapeutic targets.Topological analysis based on the PPI network revealed 22 core targets.Using KEGG enrichment analysis,165 significantly enriched pathways were identified,including the TNF and HIF-1 signaling pathways.Molecular docking analysis re-vealed high binding affinities between cordycepin and select core targets,which further corroborated by mo-lecular dynamics simulations.In vitro experiments showed that after cordycepin pretreatment,the upregu-lation of MAPK1,HIF1A,MTOR,MYC,IL10,and JUN mRNA was significantly rescued in HDM-stimulated Beas-2B cells.Conclusions Cordycepin exerts anti-asthmatic effects by targeting MAPK1 and other key molecules,thereby providing a scientific foundation for its further development and clinical application.
7.National bloodstream infection bacterial resistance surveillance report 2023: Gram-positive bacteria
Chaoqun YING ; Jinru JI ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(2):118-132
Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System(BRICS)during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute(CLSI). Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus( n=1 544,35.2%),coagulase-negative Staphylococci( n=1 441,32.9%), Enterococcus faecium( n=574,13.1%), Enterococcus faecalis( n=385,8.8%),and α-hemolytic Streptococci( n=187,4.3%). The prevalence of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)was 26.2%(405/1 544)and 69.8%(1 006/1 441),respectively. Notably,all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility(>97.0%)to cephalobiol,rifampicin,trimethoprim-sulfamethoxazole,linezolid,minocycline,tigecycline,and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium(resistance to vancomycin and teicoplanin:both 1.7%)compared to Enterococcus faecalis(both 0.3%). The detection rates of MRSA and MRCNS exhibited significant regional variations across the country( χ2=17.674 and 148.650,respectively,both P<0.001). No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA( χ2=14.111, P<0.001)and MRCNS( χ2=4.828, P=0.028)in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA( χ2=18.986, P<0.001)and MRCNS( χ2=4.477, P=0.034)in less developed regions(per capita GDP
8.National bloodstream infection bacterial resistance surveillance report (2023) : Gram-negative bacteria
Jinru JI ; Zhiying LIU ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(1):47-62
Objective:To report the results of bacterial resistant investigation collaborative system(BRICS)on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023,and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. 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 were used to analyze the data.Results:During the study period,11 492 strains of Gram-negative bacteria were collected from 60 hospitals,of which 10 098(87.9%)were Enterobacterales and 1 394(12.1%)were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli(50.0%), Klebsiella pneumoniae(26.1%), Pseudomonas aeruginosa(5.1%), Acinetobacter baumannii complex(5.0%)and Enterobacter cloacae complex(4.1%). The ESBL-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus mirablilis were 46.8%(2 685/5 741),18.3%(549/2 999)and 44.0%(77/175),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(76/5 741)and 15.0%(450/2 999);32.9%(25/76)and 78.0%(351/450)of CREC and CRKP were sensitive to ceftazidime/avibactam combination,respectively. 94.7%(72/76)and 90.2%(406/450)of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore,57.9%(44/76)and 79.1%(356/450)were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 64.6%(370/573),while more than 80.0% of CRAB complex was sensitive to tigecycline,eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 17.0%(99/581). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China,with statistically significant differences in the prevalence of CREC,CRKP,CRPA and CRAB complex( χ2=10.6,28.6,10.8 and 19.3, P<0.05). The prevalence of ESBL-producing Escherichia coli, CREC,CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals( χ2=12.5,9.8,12.7 and 57.8,all P<0.01). Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China,and Escherichia coli is ranked in the top,while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend,CREC infecton maintains a low prevalence level,and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.
9.National bloodstream infection bacterial resistance surveillance report(2022): Gram-positive bacteria
Chaoqun YING ; Yunbo CHEN ; Jinru JI ; Zhiying LIU ; 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(2):99-112
Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-positive bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-positive 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:A total of 3 163 strains of Gram-positive pathogens were collected from 51 member units,and the top five bacteria were Staphylococcus aureus( n=1 147,36.3%),coagulase-negative Staphylococci( n=928,29.3%), Enterococcus faecalis( n=369,11.7%), Enterococcus faecium( n=296,9.4%)and alpha-hemolyticus Streptococci( n=192,6.1%). The detection rates of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)were 26.4%(303/1 147)and 66.7%(619/928),respectively. No glycopeptide and daptomycin-resistant Staphylococci were detected. The sensitivity rates of Staphylococcus aureus to cefpirome,rifampin,compound sulfamethoxazole,linezolid,minocycline and tigecycline were all >95.0%. Enterococcus faecium was more prevalent than Enterococcus faecalis. The resistance rates of Enterococcus faecium to vancomycin and teicoplanin were both 0.5%(2/369),and no vancomycin-resistant Enterococcus faecium was detected. The detection rate of MRSA in southern China was significantly lower than that in other regions( χ2=14.578, P=0.002),while the detection rate of MRCNS in northern China was significantly higher than that in other regions( χ2=15.195, P=0.002). The detection rates of MRSA and MRCNS in provincial hospitals were higher than those in municipal hospitals( χ2=13.519 and 12.136, P<0.001). The detection rates of MRSA and MRCNS in economically more advanced regions(per capita GDP≥92 059 Yuan in 2022)were higher than those in economically less advanced regions(per capita GDP<92 059 Yuan)( χ2=9.969 and 7.606, P=0.002和0.006). Conclusions:Among the Gram-positive pathogens causing bloodstream infections in China, Staphylococci is the most common while the MRSA incidence decreases continuously with time;the detection rate of Enterococcus faecium exceeds that of Enterococcus faecalis. The overall prevalence of vancomycin-resistant Enterococci is still at a low level. The composition ratio of Gram-positive pathogens and resistant profiles varies slightly across regions of China,with the prevalence of MRSA and MRCNS being more pronounced in provincial hospitals and areas with a per capita GDP≥92 059 yuan.
10.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.

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