1.Establishment of a sandwich ELISA method for CHGA in saliva samples and its preliminary application in stress detection.
Niqi SHAN ; Shanshou LIU ; Yuling WANG ; Hui LIU ; Shuai WANG ; Yilin WU ; Chujun DUAN ; Hanyin FAN ; Yangmengjie JING ; Ran ZHUANG ; Chunmei ZHANG
Chinese Journal of Cellular and Molecular Immunology 2025;41(4):324-330
Objective To establish a sandwich enzyme-linked immunosorbent assay (ELISA) method for the quantitative detection of Chromogranin A (CHGA) in saliva, and to explore its preliminary application in the testing of saliva samples. Methods Recombinant human CHGA protein was used to immunize BALB/c mice, and monoclonal antibodies (mAbs) were prepared and screened using conventional hybridoma technology. A double-antibody sandwich ELISA detection method was constructed, and the matrix effect of saliva samples was optimized. This method was then applied to detect the concentration of CHGA in the saliva of stressed individuals. Results Twenty-one stable hybridoma cell lines secreting high affinity anti-human CHGA antibodies were obtained. A pair of detection antibodies with the best effect was selected, and the optimal coating concentration was determined to be 10 μg/mL, with the optimal dilution of detection antibodies being 1:32 000. The accuracy and reproducibility of this method were verified, with both intra-batch and inter-batch variation coefficients less than 15×, and the recovery rate between 80× and 120×. The matrix effect was further optimized to make it suitable for saliva sample detection. Saliva samples from individuals in different stress states were collected, and the CHGA levels were detected using the method established in this study, indicating its potential to reflect the intensity of stress. Conclusion A reliable saliva CHGA ELISA detection method has been successfully established, and its potential as a biomarker in stress-related research has been preliminarily explored.
Saliva/metabolism*
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Enzyme-Linked Immunosorbent Assay/methods*
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Humans
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Animals
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Mice, Inbred BALB C
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Mice
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Chromogranin A/immunology*
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Antibodies, Monoclonal/immunology*
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Female
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Male
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Reproducibility of Results
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Adult
2.Clinical value analysis of different MRI measurement methods in evaluating the efficacy of neoadjuvant therapy for breast cancer
Yuling DUAN ; Xuezhi ZHOU ; Yongyi LI ; Lixia MA ; Desheng YANG ; Jiao CHENG ; Yan WU ; Tao LIU ; Guoyuan JIANG ; Mei WANG
The Journal of Practical Medicine 2025;41(14):2152-2159
Objective To compare the diagnostic performance of three breast MRI measurement methods—RECIST 1.1,the optimal method,and three-dimensional(3D)volumetric assessment—in assessing the efficacy of neoadjuvant chemotherapy(NAC)in breast cancer patients,with the objective of identifying the most clinically practical approach.Methods A total of 110 breast cancer patients who underwent NAC followed by surgical treatment between 2019 and 2023 were included in the study.Breast magnetic resonance imaging(MRI)was conducted within one week before and after the completion of NAC.Tumor response was evaluated using RECIST 1.1 criteria,widely recognized as the optimal method,as well as 3D volume measurement.Pathological response was determined according to the Miller-Payne grading system.Sensitivity,specificity,accuracy,and the area under the receiver operating characteristic curve(AUC)were computed and compared using the DeLong test.Results The AUC values for RECIST 1.1,the optimal method,and 3D volumetric assessment were 0.768,0.795,and 0.883,respectively.The 3D volumetric assessment exhibited significantly better discriminative performance(P<0.05),with the highest sensitivity(98.9%),specificity(77.8%),and accuracy(95.5%).Additionally,the optimal method demonstrated superior performance over RECIST 1.1 across multiple parameters.Conclusions 3D volumetric mea-surement demonstrates superior performance compared to RECIST 1.1 and the optimal method in evaluating the response to NAC,offering a more accurate and comprehensive assessment tool.Additionally,the optimal method shows advantages over RECIST 1.1 and may serve as a practical alternative in settings where 3D software is not available.
3.Clinical value analysis of different MRI measurement methods in evaluating the efficacy of neoadjuvant therapy for breast cancer
Yuling DUAN ; Xuezhi ZHOU ; Yongyi LI ; Lixia MA ; Desheng YANG ; Jiao CHENG ; Yan WU ; Tao LIU ; Guoyuan JIANG ; Mei WANG
The Journal of Practical Medicine 2025;41(14):2152-2159
Objective To compare the diagnostic performance of three breast MRI measurement methods—RECIST 1.1,the optimal method,and three-dimensional(3D)volumetric assessment—in assessing the efficacy of neoadjuvant chemotherapy(NAC)in breast cancer patients,with the objective of identifying the most clinically practical approach.Methods A total of 110 breast cancer patients who underwent NAC followed by surgical treatment between 2019 and 2023 were included in the study.Breast magnetic resonance imaging(MRI)was conducted within one week before and after the completion of NAC.Tumor response was evaluated using RECIST 1.1 criteria,widely recognized as the optimal method,as well as 3D volume measurement.Pathological response was determined according to the Miller-Payne grading system.Sensitivity,specificity,accuracy,and the area under the receiver operating characteristic curve(AUC)were computed and compared using the DeLong test.Results The AUC values for RECIST 1.1,the optimal method,and 3D volumetric assessment were 0.768,0.795,and 0.883,respectively.The 3D volumetric assessment exhibited significantly better discriminative performance(P<0.05),with the highest sensitivity(98.9%),specificity(77.8%),and accuracy(95.5%).Additionally,the optimal method demonstrated superior performance over RECIST 1.1 across multiple parameters.Conclusions 3D volumetric mea-surement demonstrates superior performance compared to RECIST 1.1 and the optimal method in evaluating the response to NAC,offering a more accurate and comprehensive assessment tool.Additionally,the optimal method shows advantages over RECIST 1.1 and may serve as a practical alternative in settings where 3D software is not available.
4.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.
5.Changing resistance profiles of Staphylococcus isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yuling XIAO ; Mei KANG ; Yi XIE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Ping JI ; Fengbo ZHANG ; 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 ; 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(5):570-580
Objective To investigate the changing distribution and antibiotic resistance profiles of clinical isolates of Staphylococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Staphylococcus according to the unified protocol of CHINET(China Antimicrobial Surveillance Network)using disk diffusion method and commercial automated systems.The CHINET antimicrobial resistance surveillance data from 2015 to 2021 were interpreted according to the 2021 CLSI breakpoints and analyzed using WHONET 5.6.Results During the period from 2015 to 2021,a total of 204,771 nonduplicate strains of Staphylococcus were isolated,including 136,731(66.8%)strains of Staphylococcus aureus and 68,040(33.2%)strains of coagulase-negative Staphylococcus(CNS).The proportions of S.aureus isolates and CNS isolates did not show significant change.S.aureus strains were mainly isolated from respiratory specimens(38.9±5.1)%,wound,pus and secretions(33.6±4.2)%,and blood(11.9±1.5)%.The CNS strains were predominantly isolated from blood(73.6±4.2)%,cerebrospinal fluid(12.1±2.5)%,and pleural effusion and ascites(8.4±2.1)%.S.aureus strains were mainly isolated from the patients in ICU(17.0±7.3)%,outpatient and emergency(11.6±1.7)%,and department of surgery(11.2±0.9)%,whereas CNS strains were primarily isolated from the patients in ICU(32.2±9.7)%,outpatient and emergency(12.8±4.7)%,and department of internal medicine(11.2±1.9)%.The prevalence of methicillin-resistant strains was 32.9%in S.aureus(MRSA)and 74.1%in CNS(MRCNS).Over the 7-year period,the prevalence of MRSA decreased from 42.1%to 29.2%,and the prevalence of MRCNS decreased from 82.1%to 68.2%.MRSA showed higher resistance rates to all the antimicrobial agents tested except trimethoprim-sulfamethoxazole than methicillin-susceptible S.aureus(MSSA).Over the 7-year period,MRSA strains showed decreasing resistance rates to gentamicin,rifampicin,and levofloxacin,MRCNS showed decreasing resistance rates to gentamicin,erythromycin,rifampicin,and trimethoprim-sulfamethoxazole,but increasing resistance rate to levofloxacin.No vancomycin-resistant strains were detected.The prevalence of linezolid-resistant MRCNS increased from 0.2%to 2.3%over the 7-year period.Conclusions Staphylococcus remains the major pathogen among gram-positive bacteria.MRSA and MRCNS were still the principal antibiotic-resistant gram-positive bacteria.No S.aureus isolates were found resistant to vancomycin or linezolid,but linezolid-resistant strains have been detected in MRCNS isolates,which is an issue of concern.
6.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
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 ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; 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 ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% 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) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had 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 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
7.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
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 ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; 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 ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% 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) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had 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 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
8.Current status of the application of robot-assisted laparoscopic hepatectomy
Lei WANG ; Kangwei LIU ; Yuling DUAN ; Xinyao LI ; Cijun PENG
Journal of Clinical Hepatology 2021;37(11):2732-2736
Robot-assisted laparoscopy hepatectomy (RALH) is a new technique for surgical operation. Compared with conventional laparoscopic hepatectomy, RALH is more frequently used in complex liver tumor and liver tumor with special locations, but this technique is still under development and is limited by the burden of high costs and surgical devices. Meanwhile, there is a lack of generally accepted and confirmed clinical data, and therefore, the role of RALH is still under debate. This article reviews the surgical indication, learning curve, advantages, and limitations of RALH.
9.Risk factors for open pancreatic necrosectomy in patients with severe acute pancreatitis: An analysis based on the surgical step-up approach
Yuling DUAN ; Zanjie FENG ; Guoxin FAN ; Lei WANG ; Kangwei LIU ; Cijun PENG
Journal of Clinical Hepatology 2021;37(4):893-897
ObjectiveTo investigate the risk factors for open pancreatic necrosectomy (OPN), an effective treatment method for severe acute pancreatitis (SAP) after the failure of percutaneous catheter drainage (PCD), in patients with SAP. MethodsA retrospective analysis was performed for 156 patients with SAP who underwent surgical intervention based on the step-up approach in The Affiliated Hospital of Zunyi Medical University from January 1, 2010 to June 30, 2018, and according to whether OPN was performed, the patients were divided into PCD group with 126 patients and PCD+OPN group with 30 patients. Related clinical data were collected, including age, sex, etiology, blood calcium on admission, white blood cell count on admission, whether CTSI score was >7, APACHE-Ⅱ score, Ranson score, presence or absence of peripancreatic fluid accumulation, presence or absence of infection, presence or absence of multiple organ failure (MOF), and whether PCD was performed at more than 1 week after admission. The t-test was used for comparison of continuous data between groups, and the chi-square test was used for comparison of categorical data between groups; a multivariate logistic regression analysis was used to determine the independent predictive factors for OPN. ResultsThe probability of OPN was 19.2% for SAP patients in the later stage. Compared with the PCD+OPN group, the PCD group had a significantly lower proportion of patients with MOF on admission [27.0% (34/126) vs 70.0% (21/30), χ2=19.642, P<0.01] and a significantly higher proportion of patients undergoing PCD at less than 1 week after admission [61.9% (78/126) vs 20.0% (6/30), χ2=17.121, P<0.01]. MOF on admission (odds ratio [OR]=5.343, 95% confidence interval [CI]: 1.832-15.583, P<0.05), initial PCD performed at more than 1 week after admission (OR= 5.518, 95% CI: 1.742-17.477, P<0.05), and infection on admission (OR=5.016, 95% CI: 1.322-19.378, P<0.05) were independent risk factors for subsequent OPN in SAP patients. ConclusionSAP with MOF on admission, initial PCD performed at more than 1 week after admission, and SAP with infection on admission are independent risk factors for subsequent OPN in SAP patients undergoing PCD in the early stage based on the step-up approach. Timely identification of related risk factors helps to grasp the timing of OPN in clinical practice and improve the clinical prognosis of SAP patients.
10.Study on the timing of sequential LC after ERCP in elderly patients with cholecystolithiasis complicated with choledocholithiasis
Lei WANG ; Kangwei LIU ; Yuling DUAN
Journal of Clinical Surgery 2021;29(6):559-561
Objective To explore the safety and efficacy of laparoscopic cholecystectomy in different time points after endoscopic retrograde cholangiopancreatography in elderly patients with cholecystolithiasis and choledocholithiasis. Methods 99 elderly patients (≥60 years old)with cholecystolithiasis and choledocholithiasis treated by sequential LC after ERCP in the Department of Hepatobiliary and Pancreatic surgery in our hospital from January 2015 to June 2020 were analyzed. Aocording to different time points after ERCP, LC was divided into experimental group (within 1 day after ERCP) and control group (within 2-7 days after ERCP). The complications were followed up by telephone within 3 months after operation. Results After analysis,the difference between the experimental group and the control group in the total length of hospitalization [(13.0±4.6)d vs ( 15.1±4.4)d] and total hospitalization expenses (38 172.5±12 448.9) vs ( 42 535.4±8 814.6)] was statistically significant (P<0.05). However, there was no significant difference in the conversion rate of LC to laparotomy, the total postoperative complications , the length of hospital stay after LC,the amount of blood loss during LC and the time of LC operation between the two groups(P>0.05). Conclusion For elderly patients with cholecystolithiasis and choledocholithiasis, LC within 1 day after ERCP does not increase the difficulty of operation and postoperative complications,but shortens the hospitalization time, and it is economical and safe at the same time.

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