1.Effect of joint management of type 2 diabetes mellitus between specialty department and community health under National Diabetes Prevention and Control Center (DPCC) model
Ying HUANG ; Yi QIAN ; Xuchi WU ; Zhongyu ZHOU ; Cong WANG ; Lin WANG ; Caiyan HUANG ; Zhuangsen CHEN ; Yanrong ZHANG ; Shanshan WANG ; Lu WANG ; Jie WAN ; Ruihong YANG ; Huiya WANG ; Yan CHEN ; Cheng HE ; Kun FENG ; Dewen YAN
Journal of Chinese Physician 2025;27(3):338-342
Objective:To analyze the effect of joint management of type 2 diabetes mellitus (T2DM) between specialty and community under the model of National Diabetes Prevention and Control Center (DPCC).Methods:A total of 2 527 T2DM patients managed by DPCC Pingshan Center of Shenzhen from January 1, 2022 to December 31, 2024 were retrospectively included. After management, the rate of downturn, reexamination rate, blood pressure compliance rate, metabolic indicators (waist circumference, body mass index, fasting blood glucose, glycosylated hemoglobin, blood lipids) and screening rate of chronic complications of diabetes (atherosclerotic cardiovascular disease, microvascular disease, diabetic peripheral neuropathy) were analyzed. Those included 2022 ( n=564), 2023 ( n=1 477), and 2024 ( n=2 527). Results:The downturn rate in 2022, 2023 and 2024 increased year by year (22.8% vs 67.2% vs 89.9%, P<0.01), and the review rate (41.1% vs 62.2% vs 52.7%, P<0.01), complication screening rate (51.6% vs 85.3% vs 62.2%, P<0.01), blood pressure compliance rate (53.1% vs 78.0% vs 67.2%, P<0.01), body mass index compliance rate (13.2% vs 17.3% vs 28.6%, P<0.01), fasting blood glucose meeting rate (46.4% vs 60.2% vs 68.5%, P<0.01), glycated hemoglobin meeting rate (58.4% vs 63.2% vs 45.6%, P<0.01) were relatively improved. Waist circumference compliance rate (30.6% vs 27.7% vs 21.6%) and blood lipid compliance rate (33.6% vs 35.5% vs 31.9%) were not significantly improved, and the review rate, blood pressure compliance rate and complication screening rate in 2024 were lower than those in 2023 and higher than those in 2022. Conclusions:The combined management of type 2 diabetes under the DPCC model has significant effects on improving the down-conversion rate, rediagnosis rate, blood pressure compliance rate, metabolic index compliance rate and the screening rate of diabetes-related chronic complications in patients with diabetes. At the same time, it was also found that with the progress of hierarchical diagnosis and treatment, the review rate, complication screening rate, blood pressure, waist circumference, blood lipid and glycosylated hemoglobin reached the standard of patients decreased compared with the previous situation, which needs to be further analyzed and improved.
2.Evaluation of health education and health promotion effect on coal-burning pollution-induced endemic fluorosis in Ankang City, Shaanxi Province from 2020 to 2023
Ying DENG ; Lei LIANG ; Feng SU ; Tonglei ZHANG ; Zhi SHI ; Rong ZHOU ; Zhongxue FAN
Chinese Journal of Endemiology 2025;44(5):420-425
Objective:To evaluate the effectiveness of health education and health promotion for coal-burning pollution-induced endemic fluorosis (coal-burning fluorosis) in Ankang City, Shaanxi Province, and provide reference for further developing health education and health promotion measures.Methods:From 2020 to 2023, one county (district) was selected as the project county in coal-burning fluorosis area of Ankang City each year, and 3 to 5 towns of each project county were selected as the project town. Health education and health promotion activities on coal-burning fluorosis were carried out for department heads, endemic disease propaganda workers of project county, and students in grades 4 to 6 from center primary schools, local residents and migrant workers of all affected villages of project county. Before and after the implementation of health education and health promotion projects, 30 to 45 primary school students and 30 local residents from each project town were selected to conduct a questionnaire survey on the prevention and control knowledge of coal-burning fluorosis every year, and a household survey was conducted to investigate the prevalence and changes of specific behaviors of local residents who open their stoves.Results:From 2020 to 2023, the coverage rate of intervention activities for department heads, endemic disease propaganda workers, and primary school students in the project county was 100%; the coverage rate of intervention activities for local residents in the project county was 94.44% (18 271/19 346), and for migrant workers was 97.86% (8 683/8 873). The awareness rate of prevention and control knowledge of coal-burning fluorosis among primary school students and local residents after health education and health promotion in each year was significantly higher than those before health education and health promotion ( P < 0.001), and showed an increasing trend year by year (χ 2trend = 36.73, 38.47, P < 0.001). From 2020 to 2023, a total of 420 local residents were surveyed, and 110 people used open stoves. The prevalence rate of specific behaviors was 26.19%, and it showed a decreasing trend year by year (χ 2trend = 0.29, P < 0.001). After health education and health promotion, the number of people who changed their behavior during a certain period was 106, and the specific behavior change rate was 96.36% (106/110). Conclusions:The health education and health promotion on coal-burning fluorosis in Ankang City has achieved significant results. In the future, we should continue to increase investment in health education and health promotion, continuously improve the long-term mechanism of endemic disease health education and health promotion, innovate health education models, further improve the effectiveness of health promotion, and consolidate the achievements of prevention and control.
3.Statistical Quality Control Strategy of Clinical Biochemistry Detection Project Based on Risk Model
Dahai HE ; Lirui KONG ; Yan ZHANG ; Feng WU ; Chaoqiong ZHOU ; Ying HUANG ; Lin YU
Journal of Modern Laboratory Medicine 2025;40(2):202-207
Objective To define the operation scale of the biochemical test project based on the risk model,and design the statistical quality control(SQC)strategy by rationally adjusting the risk factors.Methods The σ(σ)values for the biochemistry test items were calculated based on the imprecision(CV)of internal quality control(IQC),external quality assessment(EQA)offset bias(Bias)and allowable total error(TEa)of CLIA 2019.By evaluating and adjusting the patient risk factors,designed the SQC for multiple test biochemical items representing high σ,medium σ and low σ categories.Results Clinical biochemistry testing items with different QC levels showed different σ performance,with values for P and K quality control levels 2 higher than level 1 and the remaining items all had very similar.18 projects for risk σ≥4.96:CK,LDH,GGT,AMY,AST,MG,TG,TBIL,FE,NA,UA,CREA,P,ALP,K,ALT and CA,respectively.Controlled with a QC program 13s N=2,run size was 179~1 000 samples.ALB,GLU,CL,TP and UREA need to achieve the expected operational scale by adjusting for risk factors.Conclusion The laboratory can combine program testing performance and patient safety goals,design SQC strategies for clinical biochemistry testing programs by rationally adjusting risk factors,apply as few SQC procedures for as much testing as possible,and align the laboratory workload and reporting interval with the number of patient samples.
4.Quantitative evaluation and driving path exploration on the level of the tripartite system reform in China
Ling-yun GUO ; Liu-jie FU ; Yong-yi GUAN ; Liang-ru ZHOU ; Qiu-ying ZHENG ; Rui-feng LI
Chinese Journal of Health Policy 2025;18(3):9-17
Objective:To quantitatively evaluate the level of the three medical linkage in China from 2009 to 2022,explore the influencing factors and driving paths of the three medical linkage in China,and provide a new perspective for promoting the development of the three medical linkage.Methods:An optimized coupling coordination degree model was used to calculate the coupling coordination degree between the trinity healthcare systems and different binary systems within the systems in 31 provinces of China(excluding Hong Kong,Macao and Taiwan),and the Fuzzy-set Qualitative Comparative Analysis method was used to explore the condition configurations of multi-factor-driven three medical linkage.Results:From 2009 to 2022,the coupling coordination degree between the trinity healthcare systems in each province of China generally showed an increasing trend year by year.Among the binary systems,the overall coordinated development situation between the medical and medical insurance systems was the best and the regional development was the most balanced.The coupling coordination degree gap between the trinity healthcare system and the internal binary systems among provinces gradually widened,and the multi-polarization trend intensified.The paths to promote high-level three medical linkage can be summarized into two types:internal and external balanced development type(H1)and government-led type(H2,H3),among which the H1 path with per capita GDP and health expenditure as core conditions was the most common.Conclusion:It is suggested to enhance institutional and technological innovation,and integrate resources through a cross-departmental collaboration mechanism and digital technology.Provinces should select high-level optimization paths by leveraging regional endowments to narrow the regional development gap.Meanwhile,under the impetus of high-level policies,the protection and supervision system continues to improve,thereby promoting the three medical linkage.
5.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
6.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; 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 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(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
7.Effect of joint management of type 2 diabetes mellitus between specialty department and community health under National Diabetes Prevention and Control Center (DPCC) model
Ying HUANG ; Yi QIAN ; Xuchi WU ; Zhongyu ZHOU ; Cong WANG ; Lin WANG ; Caiyan HUANG ; Zhuangsen CHEN ; Yanrong ZHANG ; Shanshan WANG ; Lu WANG ; Jie WAN ; Ruihong YANG ; Huiya WANG ; Yan CHEN ; Cheng HE ; Kun FENG ; Dewen YAN
Journal of Chinese Physician 2025;27(3):338-342
Objective:To analyze the effect of joint management of type 2 diabetes mellitus (T2DM) between specialty and community under the model of National Diabetes Prevention and Control Center (DPCC).Methods:A total of 2 527 T2DM patients managed by DPCC Pingshan Center of Shenzhen from January 1, 2022 to December 31, 2024 were retrospectively included. After management, the rate of downturn, reexamination rate, blood pressure compliance rate, metabolic indicators (waist circumference, body mass index, fasting blood glucose, glycosylated hemoglobin, blood lipids) and screening rate of chronic complications of diabetes (atherosclerotic cardiovascular disease, microvascular disease, diabetic peripheral neuropathy) were analyzed. Those included 2022 ( n=564), 2023 ( n=1 477), and 2024 ( n=2 527). Results:The downturn rate in 2022, 2023 and 2024 increased year by year (22.8% vs 67.2% vs 89.9%, P<0.01), and the review rate (41.1% vs 62.2% vs 52.7%, P<0.01), complication screening rate (51.6% vs 85.3% vs 62.2%, P<0.01), blood pressure compliance rate (53.1% vs 78.0% vs 67.2%, P<0.01), body mass index compliance rate (13.2% vs 17.3% vs 28.6%, P<0.01), fasting blood glucose meeting rate (46.4% vs 60.2% vs 68.5%, P<0.01), glycated hemoglobin meeting rate (58.4% vs 63.2% vs 45.6%, P<0.01) were relatively improved. Waist circumference compliance rate (30.6% vs 27.7% vs 21.6%) and blood lipid compliance rate (33.6% vs 35.5% vs 31.9%) were not significantly improved, and the review rate, blood pressure compliance rate and complication screening rate in 2024 were lower than those in 2023 and higher than those in 2022. Conclusions:The combined management of type 2 diabetes under the DPCC model has significant effects on improving the down-conversion rate, rediagnosis rate, blood pressure compliance rate, metabolic index compliance rate and the screening rate of diabetes-related chronic complications in patients with diabetes. At the same time, it was also found that with the progress of hierarchical diagnosis and treatment, the review rate, complication screening rate, blood pressure, waist circumference, blood lipid and glycosylated hemoglobin reached the standard of patients decreased compared with the previous situation, which needs to be further analyzed and improved.
8.Quantitative evaluation and driving path exploration on the level of the tripartite system reform in China
Ling-yun GUO ; Liu-jie FU ; Yong-yi GUAN ; Liang-ru ZHOU ; Qiu-ying ZHENG ; Rui-feng LI
Chinese Journal of Health Policy 2025;18(3):9-17
Objective:To quantitatively evaluate the level of the three medical linkage in China from 2009 to 2022,explore the influencing factors and driving paths of the three medical linkage in China,and provide a new perspective for promoting the development of the three medical linkage.Methods:An optimized coupling coordination degree model was used to calculate the coupling coordination degree between the trinity healthcare systems and different binary systems within the systems in 31 provinces of China(excluding Hong Kong,Macao and Taiwan),and the Fuzzy-set Qualitative Comparative Analysis method was used to explore the condition configurations of multi-factor-driven three medical linkage.Results:From 2009 to 2022,the coupling coordination degree between the trinity healthcare systems in each province of China generally showed an increasing trend year by year.Among the binary systems,the overall coordinated development situation between the medical and medical insurance systems was the best and the regional development was the most balanced.The coupling coordination degree gap between the trinity healthcare system and the internal binary systems among provinces gradually widened,and the multi-polarization trend intensified.The paths to promote high-level three medical linkage can be summarized into two types:internal and external balanced development type(H1)and government-led type(H2,H3),among which the H1 path with per capita GDP and health expenditure as core conditions was the most common.Conclusion:It is suggested to enhance institutional and technological innovation,and integrate resources through a cross-departmental collaboration mechanism and digital technology.Provinces should select high-level optimization paths by leveraging regional endowments to narrow the regional development gap.Meanwhile,under the impetus of high-level policies,the protection and supervision system continues to improve,thereby promoting the three medical linkage.
9.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
10.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; 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 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(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

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