1.PI Chiheng's Experience in Staged Treatment of Diabetic Nephropathy with the Method of Warming Yang, Nourishing Yin,and Invigorating Blood
Journal of Traditional Chinese Medicine 2025;66(7):669-673
This paper summarized Professor PI Chiheng's experience in treating diabetic nephropathy (DN) using the method of warming yang, nourishing yin, and invigorating blood by stages. It is believed that yang deficiency and yin depletion are the key pathological mechanisms of DN, with blood stasis running throughout the disease's progression. The general treatment principle is to warm yang, nourish yin, and invigorate blood, with different emphases at each stage. For early stage, the disease is characterized by spleen qi deficiency and insufficiency of qi and yin, which could be treated by modified Shenqi Dihuang Decoction (参芪地黄汤) to tonify qi and invigorate blood, strengthen yang and consolidate yin; for middle stage, the disease is marked by spleen and kidney yang deficiency with internal dampness accumulation, which could be treated by modified Zhenwu Decoction (真武汤) and Sanren Decoction (三仁汤) warming yang and to resolve dampness and unblock meridians; for the late stage, the disease is characterized by blood stasis and toxin accumulation with deficiency of both yin and yang, which could be treated by modified Jisheng Shenqi Pill (济生肾气丸) to eliminate pathological masses and remove toxins, warm yang and nourish yin. Additionally, traditional Chinese medicine therapies such as rubbing with ointment (Gao Mo therapy) are utilized as adjunct treatments, treating the root and branch simultaneously and combining internal and external approaches.
2.Equivalence of SYN008 versus omalizumab in patients with refractory chronic spontaneous urticaria: A multicenter, randomized, double-blind, parallel-group, active-controlled phase III study.
Jingyi LI ; Yunsheng LIANG ; Wenli FENG ; Liehua DENG ; Hong FANG ; Chao JI ; Youkun LIN ; Furen ZHANG ; Rushan XIA ; Chunlei ZHANG ; Shuping GUO ; Mao LIN ; Yanling LI ; Shoumin ZHANG ; Xiaojing KANG ; Liuqing CHEN ; Zhiqiang SONG ; Xu YAO ; Chengxin LI ; Xiuping HAN ; Guoxiang GUO ; Qing GUO ; Xinsuo DUAN ; Jie LI ; Juan SU ; Shanshan LI ; Qing SUN ; Juan TAO ; Yangfeng DING ; Danqi DENG ; Fuqiu LI ; Haiyun SUO ; Shunquan WU ; Jingbo QIU ; Hongmei LUO ; Linfeng LI ; Ruoyu LI
Chinese Medical Journal 2025;138(16):2040-2042
3.Guidelines for the diagnosis and treatment of prurigo nodularis.
Li ZHANG ; Qingchun DIAO ; Xia DOU ; Hong FANG ; Songmei GENG ; Hao GUO ; Yaolong CHEN ; Chao JI ; Chengxin LI ; Linfeng LI ; Jie LI ; Jingyi LI ; Wei LI ; Zhiming LI ; Yunsheng LIANG ; Jianjun QIAO ; Zhiqiang SONG ; Qing SUN ; Juan TAO ; Fang WANG ; Zhiqiang XIE ; Jinhua XU ; Suling XU ; Hongwei YAN ; Xu YAO ; Jianzhong ZHANG ; Litao ZHANG ; Gang ZHU ; Fei HAO ; Xinghua GAO
Chinese Medical Journal 2025;138(22):2859-2861
4.Characteristics of first-time callers with suicidal ideation to psychological assistance hotline in Henan Province
Kunya LIU ; Xiaoniu LI ; Qingqing ZHANG ; Lei ZHANG ; Huiping CHENG ; Shiyun WANG ; Yunsheng HOU ; Ying XU ; Ruiling ZHANG
Chinese Mental Health Journal 2025;39(5):398-404
Objective:To examine the spatial and temporal distribution characteristics of first-time callers with suicidal ideation and risk factors related to suicidal ideation in a psychological assistance hotline in Henan Province.Methods:The computerised counselling operating system of the Henan Provincial Psychological Assis-tance Hotline was used to extract data from 31 401 callers who called the hotline between January 2020 and October 2023.A circular distribution and kernel density analysis were employed to investigate the spatial and temporal distri-bution of first-time callers with suicidal ideation.Binary logistic regression analysis was employed to investigate the risk factors for suicidal ideation.Results:A total of 5 494 first-time callers were included in the study,of whom 1 697(30.9%)reported suicidal ideation in the previous two weeks.The temporal distribution of suicidal ideation calls indicated a peak between 12:36 and 01:08.The weekly distribution further revealed that the majority of calls occurred on Fridays.In terms of spatial distribution,the primary hotspots for callers with suicidal ideation were clus-tered around Zhengzhou and Xinxiang.Meanwhile,the secondary hotspots exhibited a dispersed distribution across multiple centers within the province.Logistic regression analysis revealed that being under 20 years old(OR=11.85),being unemployed(OR=1.78),having psychological issues(OR=5.03),experiencing family relation-ship problems(OR=3.67),and facing economic hardships(OR=7.08)were risk factors for suicidal ideation.Conclusion:The time distribution of calls from individuals with suicidal ideation to the psychological as-sistance hotline in Henan Province exhibits a centralized trend,while the spatial distribution of calls demonstrates an imbalance.When receiving initial calls from individuals with suicidal ideation,particular attention should be paid to those aged 20 years old or younger,those who are unemployed,and those experiencing psychiatric,psychological,familial,and economic difficulties.
5.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; 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 2025;25(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
6.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; 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 ; 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 WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.
7.Research Progress of Chinese Medicine in Treating Influenza
Wenyu WU ; Peng WU ; Nuoran LI ; Yunsheng XU ; Zhenyang WANG ; Kai WANG ; Shaofeng ZHAN
Journal of Nanjing University of Traditional Chinese Medicine 2025;41(11):1613-1632
Influenza(flu)is an acute respiratory infection caused by influenza viruses,characterized by high morbidity,strong trans-mission and general susceptibility of the population,and often accompanied by clinical symptoms such as fever,cough and muscle aches,etc.With the global pandemic of influenza,it has become a major challenge in the field of global public health,and therefore,it is particularly important to explore effective treatment methods.Chinese medicine has thousands of years of experience in treating in-fectious diseases and plays an important role in the prevention and treatment of influenza.This paper provides a comprehensive and systematic review of the Chinese medicine name,etiology,identification and typing,treatment methods and mechanism of action of in-fluenza,aiming to make up for the lack of the current summary of Chinese medicine treatment of influenza,with a view to providing cer-tain ideas and theoretical basis for the study of Chinese medicine treatment of influenza.
8.Predictive value of whole blood cell derived inflammatory markers in combination with NT-proBNP on the prognosis of patients with chronic heart failure
Zhibin LIN ; Zhonghua TENG ; Yanru XU ; Yunsheng DENG ; Guilian LIANG ; Hengyan DENG ; Qingchun ZENG
Chinese Journal of Cardiology 2025;53(2):143-150
Objective:To evaluate the predictive value of whole blood cell derived inflammatory marker (including systemic immunoinflammatory index (SII), systemic inflammatory response index (SIRI), neutrophil count/lymphocyte count (NLR), platelet count/lymphocyte count (PLR), and monocyte count/lymphocyte count (MLR)) and in combination with N-terminal pro-B-type natriuretic peptide (NT-proBNP) on the prognosis of patients with chronic heart failure.Methods:This study was a retrospective cohort study. Patients with chronic heart failure hospitalized in the Department of Cardiovascular Medicine, Nanfang Hospital, Southern Medical University from January 2019 to August 2022 were enrolled. Patients were followed up and were divided into survival group and death group according to the follow-up results. Clinical characteristics of the two groups were compared. Receiver operating characteristic (ROC) curve was used to determine the optimal cut-off value of each whole blood cell derived inflammatory marker for predicting all-cause death in patients with chronic heart failure. Kaplan-Meier survival curve was drawn, and log-rank test was used to compare the difference in survival of chronic heart failure patients with different levels of whole blood cell derived inflammatory markers. Univariate and multivariate Cox proportional hazards models were used to analyze the effects of whole blood cell derived inflammatory markers and NT-proBNP on the all-cause death of patients with chronic heart failure. ROC curve was used to analyze the predictive value of whole blood cell derived inflammatory markers combined with NT-proBNP on the prognosis of patients with chronic heart failure.Results:A total of 324 patients with heart failure aged (64.76±13.78) years were enrolled, with 212 males (65.43%). 297 patients (91.67%) completed follow-up, 27 patients (8.33%) were lost to follow-up. The follow-up time was 24.0 (18.0, 41.8) months. There were 258 patients in the survival group and 66 patients in the death group. The optimal cut-off values of SII, SIRI, NLR, PLR and MLR determined by ROC curve were 739.83, 1.65, 3.14, 151.95 and 0.37, respectively. Kaplan-Meier survival curve analysis showed that patients with chronic heart failure with high levels of SII (≥739.83), SIRI (≥1.65), NLR (≥3.14), PLR (≥151.95) and MLR (≥0.37) had higher incidence of all-cause death than patients with low levels of inflammatory markers (all P<0.001). Multivariate Cox proportional hazard regression analysis showed that age ( HR=1.04, 95% CI 1.01-1.06, P=0.002), NT-proBNP ( HR=2.93, 95% CI 1.64-5.23, P<0.001), SII≥739.83 ( HR=3.27, 95% CI 1.18-9.02, P=0.022) and PLR≥151.95 ( HR=2.67, 95% CI 1.02-6.96, P=0.045) were independent predictors of all-cause death in patients with chronic heart failure. ROC curve analysis showed that the predictive value of SII and PLR combined with NT-proBNP ( AUC=0.850) for the prognosis of patients with chronic heart failure was better than that of SII ( AUC=0.779)、PLR ( AUC=0.782)、NT-proBNP ( AUC=0.727) and CRP ( AUC=0.668) alone (all P<0.001). Conclusions:Whole blood cell derived inflammatory markers——SII, PLR, and NT-pro BNP were independently associated with all-cause death in patients with chronic heart failure. SII and PLR can independently predict the prognosis of patients with chronic heart failure, combination of SII and PLR with NT-pro BNP has better predictive value for the prognosis of patients with chronic heart failure.
9.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; 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 2025;25(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
10.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; 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 ; 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 WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

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