2.Predictive value of atherogenic index of plasma combined with novel inflammatory indexes for MACE in ACS patients
Jing LI ; Shuai LIU ; Na LI ; Fang MENG ; Rong-xia WANG ; Jian-ping FU
Chinese Journal of cardiovascular Rehabilitation Medicine 2025;34(5):629-635
Objective:To explore the predictive value of atherogenic index of plasma(AIP)combined with neutro-phil/HDL-C ratio(NHR),lymphocyte/HDL-C ratio(LHR)and monocyte/HDL-C ratio(MHR)for major adverse cardiovascular events(MACE)in patients with acute coronary syndrome(ACS).Methods:This retrospec-tive study enrolled 320 patients underwent coronary angiography in Department of Cardiovascular Medicine,Harri-son International Peace Hospital between January 2021 and December 2022,including 215 ACS patients and 105 pa-tients without ACS;according to Gensini score,ACS patients were divided into low risk group(n=50),medium risk group(n=70)and high risk group(n=95).According to the presence of MACE within 1 year,patients were divided into MACE group(n=55)and no MACE group(n=160).After admission,blood routine,blood lipids,C-reactive protein(CRP)and endothelin-1(ET-1)levels were measured,then NHR,LHR,MHR and AIP were calculated.Spearman method was used to analyze the association of above-mentioned indexes with Gensini score;stepwise Logistic regression was used to analyze the influencing factors of MACE within 1 year in ACS patients;and ROC curve was used to analyze the predictive value of single and combined detection of above indexes for MACE within 1 year in ACS patients.Results:Compared to patients in no ACS group,those in ACS group had significantly higher BMI[(23.59±0.85)kg/m2 vs.(21.57±1.16)kg/m2],proportions of hypertension(57.67%vs.13.33%),diabetes(23.26%vs.8.57%),NHR[(12.09±3.46)vs.(3.81±1.29)],MHR[(0.70±0.18)vs.(0.33±0.10)],LHR[(0.79±0.21)vs.(0.40±0.09)],AIP[(0.21±0.06)vs.(0.11±0.02)],CRP[(9.82±3.09)mg/L vs.(2.20±0.58)mg/L],ET-1[(31.25±10.34)μg/L vs.(10.60±1.96)μg/L](P<0.001 all).Compared to those in no MACE group,patients in MACE group had significantly higher NHR[(17.33±3.87)vs.(10.12±2.68)],MHR[(0.93±0.24)vs.(0.61±0.13)],LHR[(1.05±0.27)vs.(0.71±0.16)],AIP[(0.28±0.04)vs.(0.17±0.02)],CRP[(15.52±3.83)mg/L vs.(7.69±2.40)mg/L],ET-1[(46.68±9.51)μg/L vs.(25.47±4.66)μg/L]levels(P<0.001 all).Spearman correlation analysis showed that NHR,MHR,LHR and AIP were significant positively correlated with Gensini score(r=0.837~0.868,P<0.001 all).Stepwise Logistic regression analysis showed that NHR(OR=1.225,95%CI 1.016~1.550,P=0.035),AIP(OR=2.632,95%CI 1.055~6.566,P=0.038)were independent risk factors for MACE within 1 year in ACS patients.ROC curve shows that AUC of AIP combined with NHR,MHR and LHR predicting MACE within 1 year in ACS patients was 0.786(95%CI 0.725~0.839),which was significantly higher than those of NHR(AUC 0.768,95%CI 0.706~0.823),LHR(AUC 0.749,95%CI 0.686~0.806)and AIP(AUC 0.764,95%CI 0.701~0.819)alone(Z=2.597,2.687,1.965,P<0.05 or<0.01).Conclusion:AIP combined with NHR,MHR and LHR have certain predictive value for MACE within 1 year in ACS patients.
3.Predictive value of atherogenic index of plasma combined with novel inflammatory indexes for MACE in ACS patients
Jing LI ; Shuai LIU ; Na LI ; Fang MENG ; Rong-xia WANG ; Jian-ping FU
Chinese Journal of cardiovascular Rehabilitation Medicine 2025;34(5):629-635
Objective:To explore the predictive value of atherogenic index of plasma(AIP)combined with neutro-phil/HDL-C ratio(NHR),lymphocyte/HDL-C ratio(LHR)and monocyte/HDL-C ratio(MHR)for major adverse cardiovascular events(MACE)in patients with acute coronary syndrome(ACS).Methods:This retrospec-tive study enrolled 320 patients underwent coronary angiography in Department of Cardiovascular Medicine,Harri-son International Peace Hospital between January 2021 and December 2022,including 215 ACS patients and 105 pa-tients without ACS;according to Gensini score,ACS patients were divided into low risk group(n=50),medium risk group(n=70)and high risk group(n=95).According to the presence of MACE within 1 year,patients were divided into MACE group(n=55)and no MACE group(n=160).After admission,blood routine,blood lipids,C-reactive protein(CRP)and endothelin-1(ET-1)levels were measured,then NHR,LHR,MHR and AIP were calculated.Spearman method was used to analyze the association of above-mentioned indexes with Gensini score;stepwise Logistic regression was used to analyze the influencing factors of MACE within 1 year in ACS patients;and ROC curve was used to analyze the predictive value of single and combined detection of above indexes for MACE within 1 year in ACS patients.Results:Compared to patients in no ACS group,those in ACS group had significantly higher BMI[(23.59±0.85)kg/m2 vs.(21.57±1.16)kg/m2],proportions of hypertension(57.67%vs.13.33%),diabetes(23.26%vs.8.57%),NHR[(12.09±3.46)vs.(3.81±1.29)],MHR[(0.70±0.18)vs.(0.33±0.10)],LHR[(0.79±0.21)vs.(0.40±0.09)],AIP[(0.21±0.06)vs.(0.11±0.02)],CRP[(9.82±3.09)mg/L vs.(2.20±0.58)mg/L],ET-1[(31.25±10.34)μg/L vs.(10.60±1.96)μg/L](P<0.001 all).Compared to those in no MACE group,patients in MACE group had significantly higher NHR[(17.33±3.87)vs.(10.12±2.68)],MHR[(0.93±0.24)vs.(0.61±0.13)],LHR[(1.05±0.27)vs.(0.71±0.16)],AIP[(0.28±0.04)vs.(0.17±0.02)],CRP[(15.52±3.83)mg/L vs.(7.69±2.40)mg/L],ET-1[(46.68±9.51)μg/L vs.(25.47±4.66)μg/L]levels(P<0.001 all).Spearman correlation analysis showed that NHR,MHR,LHR and AIP were significant positively correlated with Gensini score(r=0.837~0.868,P<0.001 all).Stepwise Logistic regression analysis showed that NHR(OR=1.225,95%CI 1.016~1.550,P=0.035),AIP(OR=2.632,95%CI 1.055~6.566,P=0.038)were independent risk factors for MACE within 1 year in ACS patients.ROC curve shows that AUC of AIP combined with NHR,MHR and LHR predicting MACE within 1 year in ACS patients was 0.786(95%CI 0.725~0.839),which was significantly higher than those of NHR(AUC 0.768,95%CI 0.706~0.823),LHR(AUC 0.749,95%CI 0.686~0.806)and AIP(AUC 0.764,95%CI 0.701~0.819)alone(Z=2.597,2.687,1.965,P<0.05 or<0.01).Conclusion:AIP combined with NHR,MHR and LHR have certain predictive value for MACE within 1 year in ACS patients.
4.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
5.Clinical application of CT angiography-derived fractional flow reserve in evaluating the risk stratification of coronary artery stenosis and the myocardial function
Yongguang GAO ; Ping XIA ; Yibing SHI ; Yu LI ; Jinyao ZHANG ; Yufei FU ; Yayong HUANG ; Yuanshun XU ; Gutao LI
Journal of Interventional Radiology 2024;33(9):956-960
Objective To discuss the clinical application of coronary CT angiography(CCTA)-derived fractional flow reserve(CT-FFR)in evaluating the risk stratification of the coronary artery stenosis and atherosclerotic plaque quantitative parameters.Methods A total of 122 patients,who received CCTA examination at the Xuzhou Municipal Central Hospital of China,were enrolled in this study.The patients were divided into non-ischemia group(CT-FFR>0.8,n=66)and ischemia group(CT-FFR0.8,n=56).The characteristics of atherosclerotic plaque were compared between the two groups.Logistic regression analysis was used to analyze the correlation between plaque characteristics and ischemic lesions.Results There were 218 vessels having a CT-FFR>0.8 and 174 vessels having a CT-FFR ≤0.8.Statistically significant differences in the total plaque volume,calcified plaque volume,plaque length,and stenosis ratio>50%existed between the two groups(all P<0.05).Logistic regression analysis indicated that the total plaque volume,calcified plaque volume,plaque length,and stenosis ratio>50%were the risk factors for myocardial ischemia.Conclusion CT-FFR can be used for the risk stratification of coronary stenosis and atherosclerotic plaque characteristics,which can evaluate the local myocardial blood supply condition from the anatomical stenosis and functional level so as to optimize the diagnosis and treatment measures.
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.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
8.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.
9.Analysis on the status quo of the awareness rate of core knowledge of cancer prevention and treatment and its influencing factors among residents in Liaoning Province in 2021.
Meng Dan LI ; Ping NI ; Hui Hui YU ; Zhi Fu YU ; Ji Xu SUN ; Ming Yu BAI ; Shan BAI ; Xiao Xia AN ; Yan Hong SHI ; You Yong LIU
Chinese Journal of Preventive Medicine 2023;57(1):22-28
Objective: To analyze the status quo of the knowledge and related factors of cancer prevention and treatment among residents in Liaoning Province in 2021. Methods: From August to November 2021, through network sampling method, 17 474 permanent residents aged 15-69 years in Liaoning Province were surveyed. The WeChat public account was used to collect information such as demographic characteristics and core knowledge of cancer prevention and treatment. The Chi-square test was used to compare the difference of the level of the cancer prevention and treatment knowledge among different groups. The multivariate logistic regression model was used to analyze the related factors. Results: Among the 17 474 subjects, 43.1% (7 528) were male and 58.7% (10 262) were urban residents. The overall awareness rate was 72.3%, and the awareness rate of cancer cognition, prevention, early diagnosis and treatment, cancer management and rehabilitation were 71.4%, 67.6%, 72.7%, 83.4% and 63.5%, respectively. The multivariate logistic regression model showed that the residents who were man (OR: 0.850, 95%CI: 0.781-0.925), in rural areas (OR: 0.753, 95%CI: 0.694-0.817), 55-59 years old (OR: 0.851, 95%CI: 0.751-0.963), quitters (OR: 0.721, 95%CI: 0.640-0.813) and smoker (OR: 0.724, 95%CI: 0.654-0.801) had lower awareness rates, while the residents who were 35-54 years old (OR: 1.312, 95%CI: 1.202-1.432), with an educational level of junior high school/senior high school/college degree or above (OR: 1.834-5.130, 95%CI: 1.575-6.047), technical personnel (OR: 1.592, 95%CI: 1.367-1.854), civil servant/institution staff (OR: 1.282, 95%CI: 1.094-1.503), enterprise/business/service staff (OR: 1.218, 95%CI: 1.071-1.385), retired (OR: 1.324, 95%CI: 1.114-1.573) and with family history of cancer (OR: 1.369, 95%CI: 1.266-1.481) had higher awareness rates. Conclusion: The level of the awareness of core knowledge of cancer prevention and treatment among residents in Liaoning Province has met the requirements of the Healthy China Action. Region, gender, education level, age, family history of cancer and smoking are relevant factors.
Adult
;
Female
;
Humans
;
Male
;
Middle Aged
;
China
;
Health Knowledge, Attitudes, Practice
;
Neoplasms/prevention & control*
;
Surveys and Questionnaires
;
Adolescent
;
Young Adult
;
Aged
10.ETCM v2.0: An update with comprehensive resource and rich annotations for traditional Chinese medicine.
Yanqiong ZHANG ; Xin LI ; Yulong SHI ; Tong CHEN ; Zhijian XU ; Ping WANG ; Meng YU ; Wenjia CHEN ; Bing LI ; Zhiwei JING ; Hong JIANG ; Lu FU ; Wenjing GAO ; Yanhua JIANG ; Xia DU ; Zipeng GONG ; Weiliang ZHU ; Hongjun YANG ; Haiyu XU
Acta Pharmaceutica Sinica B 2023;13(6):2559-2571
Existing traditional Chinese medicine (TCM)-related databases are still insufficient in data standardization, integrity and precision, and need to be updated urgently. Herein, an Encyclopedia of Traditional Chinese Medicine version 2.0 (ETCM v2.0, http://www.tcmip.cn/ETCM2/front/#/) was constructed as the latest curated database hosting 48,442 TCM formulas recorded by ancient Chinese medical books, 9872 Chinese patent drugs, 2079 Chinese medicinal materials and 38,298 ingredients. To facilitate the mechanistic research and new drug discovery, we improved the target identification method based on a two-dimensional ligand similarity search module, which provides the confirmed and/or potential targets of each ingredient, as well as their binding activities. Importantly, five TCM formulas/Chinese patent drugs/herbs/ingredients with the highest Jaccard similarity scores to the submitted drugs are offered in ETCM v2.0, which may be of significance to identify prescriptions/herbs/ingredients with similar clinical efficacy, to summarize the rules of prescription use, and to find alternative drugs for endangered Chinese medicinal materials. Moreover, ETCM v2.0 provides an enhanced JavaScript-based network visualization tool for creating, modifying and exploring multi-scale biological networks. ETCM v2.0 may be a major data warehouse for the quality marker identification of TCMs, the TCM-derived drug discovery and repurposing, and the pharmacological mechanism investigation of TCMs against various human diseases.

Result Analysis
Print
Save
E-mail