1.Analysis of undernutrition and associated factors among left behind and nonleftbehind primary and secondary school students in the Nutrition Improvement Program areas in central and western China
Chinese Journal of School Health 2026;47(3):327-331
Objective:
To investigate the prevalence of undernutrition and its associated factors among left behind and non left behind primary and secondary school students in the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) areas of central and western China, so as to provide evidence for improving the nutritional status of children and adolescents.
Methods:
A survey was conducted among 123 782 students selected by random cluster sampling method in grades 3-9 from NIPRCES in central (Hebei, Shanxi, Heilongjiang, Jilin, Anhui, Jiangxi, Henan, Hunan, Hubei, and Hainan) and western (Gansu, Guangxi, Inner Mongolia, Ningxia, Tibet, Shaanxi, Guizhou, Sichuan, Xinjiang, the Xinjiang Production and Construction Corps, Yunnan, Qinghai, and Chongqing) China in 2023. Anthropometric measurements and questionnaires were used to assess nutritional and dietary status. The prevalence of undernutrition was compared between left behind and non left behind students by Chi square test, and associated factors were analyzed by three level Logistic mixed effects model.
Results:
The prevalence of undernutrition was 8.5% (4 326) in left behind students and 8.1% (5 905) in non left behind students. Three level Logistic mixed effect model analysis showed that whether left behind or non left behind, the undernutrition rates of primary and secondary students in western regions were higher than those of students in central regions [ OR (95% CI )=1.72(1.57-1.87),2.25(2.07- 2.43 )]; the undernutrition risk was lower for those whose fathers had a cultural level of high school or above [ OR (95% CI )=0.69(0.62-0.77),0.90(0.82-0.98)] or junior high school [ OR (95% CI )=0.72(0.66-0.79),0.92(0.85-0.99)] compared to those with primary school or below; picky eating or selective eating increased the risk of undernutrition [ OR (95% CI )=2.36(2.07-2.68),2.28(2.04-2.55)], and primary and secondary school students without nutritional content in health education classes had higher rates of undernutrition [ OR (95% CI )=1.12(1.03-1.23),1.09(1.01-1.17)](all P <0.05).
Conclusion
The prevalence of undernutrition is slightly higher in left behind primary and secondary students than in non left behind primary and secondary students in central and western NIPRCES areas, with variations across different characteristics.
2.Temporal trends in the frequency of meat, egg and milk consumption among primary and secondary school students in rural central and western China, 2015-2023
Chinese Journal of School Health 2026;47(3):332-336
Objective:
To analyze the trends of the frequency of meat, egg, and milk consumption among rural primary and junior high school students in central and western China covered by the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) from 2015 to 2023, so as to provide basis for formulating more targeted nutrition intervention policies and health education strategies.
Methods:
Using data from six rounds of monitoring and evaluation (2015-2021 and 2023), the study included 323 870 students from grade 3 to 9 across 22 provinces (autonomous regions and municipalities) in central and western China. The consumption frequencies of meat, egg, and milk over the past week were collected via questionnaires. The Cochran-Armitage trend test was used to analyze temporal trends, and multivariable Logistic regression models were employed to analyze factors associated with the frequency of meat, egg and milk consumption and to test for interaction effects between the year and gender, region, and grade level.
Results:
From 2015 to 2023, the proportion of students consuming meat, egg, and milk ≥1 time/day increased from 23.20 %, 10.71%, and 0.74% to 35.53%, 22.09%, and 26.63%, respectively. Trend tests indicated a significant upward trend for the daily intake of all three food categories for meat, egg and milk over the years ( Z =67.18, 64.90, 93.14, all P <0.01). Multivariable Logistic regression analysis showed that the daily meat intake was lower in the central region than in the western region ( OR=0.77, 95%CI =0.76-0.78), whereas the daily intake of eggs ( OR=1.19, 95%CI =1.17-1.22) and milk ( OR= 1.27 , 95%CI =1.24-1.29) was higher in the central region (all P <0.05). Compared with grade 3-4 students, junior high school students had lower daily intake of meat, eggs, and milk≥1 time/day ( OR =0.95, 0.77, 0.77, all P <0.05), with a declining trend as grade increased. Girls also had lower daily intake of meat, eggs, and milk ≥1 time/day than boys ( OR =0.95,0.93,0.91, all P < 0.05). Significant interactions were observed between year and region, as well as between year and grade (all P <0.05).
Conclusion
From 2015 to 2023, the NIPRCES improved the intake level of among rural students, but the situation of relatively insufficient intake of egg and milk among females, junior high school students and those in the western region still exists.
3.Spinal muscular atrophy with lower extremity predominance associated with BICD2 mutation: A case report
Journal of Apoplexy and Nervous Diseases 2026;43(1):76-80
Spinal muscular atrophy (SMA) is characterized by muscle atrophy and weakness caused by degeneration of the anterior horn cells of the spinal cord, and spinal muscular atrophy with lower extremity predominance (SMALED) accounts for less than 2% of all SMA cases.Due to the rarity of the disease and varying severities of its clinical phenotype, misdiagnosis or missed diagnosis is often observed in clinical practice. In this case, a male patient aged 19 years was admitted due to “weakness in both lower limbs for more than 2 years and aggravation for more than 2 months”. Neurophysical examination showed low muscle strength and muscle atrophy of lower limbs, with negative pathological signs or sensory disorders. Electromyography examination revealed neurogenic damage in both lower limbs, and the clinical and electrophysiological features of the patient were consistent with the features of SMALED. Genetic testing revealed BICD2 gene mutation, and the patient was diagnosed with SMALED2. There was no aggravation of clinical symptoms at follow-up half a year later. This case report aims to improve the understanding and diagnosis of this disease among clinicians.
4.Expert Consensus on Neurocritical Care Monitoring and Management in Beijing and Tibet(2025)
Drolma PHURBU ; Wenjin CHEN ; Heng ZHANG ; Jian ZHANG ; Xiaomeng WANG ; Guoying LIN ; Wenjun PAN ; Xiying GUI ; Xin CAI ; Chodron TENZIN ; Jianlei FU ; Qianwei LI ; TSEYANG ; Yijun LIU ; Bo LIU ; Tsering DROLMA ; Yudron SONAM ; KYILV ; Samdrup TSERING ; Wa DA ; Juan GUO ; Cheng QIU ; Huan CHEN ; Xiaoting WANG ; Yangong CHAO ; Dawei LIU ; Wenzhao CHAI ; Chenggong HU ; Wanhong YIN ; Shihong ZHU
Medical Journal of Peking Union Medical College Hospital 2026;17(1):59-72
Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.
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.The correlation between carotid plaque parameters of dual-energy CT angiography and the occurrence of acute stroke events
He ZHANG ; Juan LONG ; Dexing ZHOU ; Pan YU ; Xuefu XIA ; Cong SONG ; Yong WANG ; He ZHANG ; Lili ZHU ; Chunfeng HU ; Kai XU ; Yankai MENG
Journal of Practical Radiology 2025;41(6):910-914
Objective To investigate the correlation between dual-energy computed tomography angiography(CTA)parameters of carotid plaques and acute stroke events.Methods A retrospective analysis was conducted on the clinical and imaging data of patients who underwent dual-energy head and neck CTA and brain MRI scans.Utilizing the Siemens workstation(Syngo.Via VB40B),region of interest(ROI)were placed on the thickest slice of the carotid plaque in the axial plane to obtain parameters such as fat fraction(FF),virtual non-contrast(VNC)value,iodine concentration(IC),electron density(Rho),effective atomic number(Zeff),dual energy index(DEI),spectral curve,and corresponding CT values at 40 keV(40 keVHU)and 90 keV(90 keVHU).The slope of the energy spectrum curve(λ)was calculated within the 40 keV-90 keV range.Patients with acute cerebral infarction(ACI)in the ipsilateral anterior circulation territory were classified into the ACI group,while those without were classified into the non-acute cerebral infarction(NACI)(NACI group).Qualitative data were analyzed using the x2 test,and quantitative data were analyzed using the t-test.The predictive performance was assessed using the area under the curve(AUC)of the receiver operating characteristic(ROC)curve,and the differences between different ROC curves were compared using the DeLong test.Results A total of 72 patients were included,with 21 in the ACI group and 51 in the NACI group.The mean values of FF,Zeff,and 40 keVHU in the ACI group were greater than those in the NACI group.Statistically significant differences were observed between the groups for Zeff,DEI,40 keVHU,and λ(P<0.05).40 keVHU demonstrated the highest predictive performance,and the AUC,sensitivity,and specificity was 0.789,81.0%,and 74.5%,respectively.A combined variable constructed through logistic regression analysis yielded an AUC,sensitivity,and specificity of 0.796,85.7%,and 70.6%,respectively,with no significant statistical differences compared to single factor variables.Conclusion Dual-energy CTA parameters of carotid plaques may aid in predicting intraplaque hemorrhage(IPH)and the occurrence of acute stroke events.
8.Practice of Cost Accounting in the"Integrated Ward"Department
Chinese Health Economics 2025;44(3):77-80,84
The"integrated ward"model breaks the traditional disease diagnosis and treatment model centered on a single discipline,and multiple disciplines carry out diagnosis and treatment work for the same patient at the same time and place,posing new challenges to departmental cost accounting.It is feasible to simultaneously set up integrated ward units,various integrated subject units,and nursing units on the accounting unit.The inpatient departments are divided into fusion ward units and general ward units.Each ward unit is divided into professional groups and nursing groups,forming a two-level,dual dimensional,relatively independent departmental accounting unit.Revenue recognition,cost collection,and allocation are carried out separately.Finally,the nursing group costs are allocated to different medical groups,while the revenue and costs of fusion wards and various traditional disciplines are calculated,providing data support for optimizing resource allocation and disciplinary development.
9.Clinicopathologic analysis of 19 cases of urachal adenocarcinoma
Xiang LI ; Ying HUANG ; Weiyu PAN ; Juan YU ; Xinxin GUO ; Xiaolei ZHANG ; Licheng SHEN ; Yingyong HOU ; Jun HOU
Chinese Journal of Clinical and Experimental Pathology 2025;41(5):571-576
Purpose To explore the clinical and pathological features,differential diagnosis,treatment methods and prognosis of urachal adenocarcinoma.Methods Nineteen cases of urachal adenocarcinoma were collected and an-alyzed by combining clinical symptoms,auxiliary examinations,histology,immunohistochemical,and genetic testing and 11 cases of bladder adenocarcinomas.Results Among the 19 patients(15 males,4 females;age range:33-75 years,mean:55 years),tumors were located at the dome or anterior wall of the bladder.Histological subtypes includ-ed mucinous adenocarcinoma(6 cases),adenocarcinoma not otherwise specified(4 cases),enteric-type adenocarci-noma(6 cases),adenocarcinoma with focal mucinous differentiation(1 case),adenocarcinoma with signet-ring cell carcinoma(1 case),and metastatic urachal adenocarcinoma(1 case).Immunophenotypic analysis revealed membra-nous positivity for β-catenin,diffuse positivity for CK34βE 12,MUC-2,and CK20,focal CK7 positivity in some cases,and rare GATA-3 positivity.Mutations in p53 were observed,while KRAS,NRAS,BRAF,and PIK3CA mutations were absent.In colorectal adenocarcinomas,CK34βE12 positivity was 40%,nuclear β-catenin positivity was 48%,and MUC-2 expression was approximately 50%.In bladder adenocarcinomas,GATA-3 and MUC-2 positivity rates were 45%and 63.6%,respectively.Conclusion Distinguishing urachal adenocarcinoma from colorectal and primary bladder adenocarcinomas remains challenging.Urachal adenocarcinoma should be suspected in patients with anterior bladder wall or dome lesions,gross hematuria,or mucinuria.No definitive diagnostic markers currently exist for ura-chal adenocarcinoma.Immunophenotypic features such as membranous β-catenin,MUC-2,and CK7 positivity may fa-vor urachal adenocarcinoma over colorectal adenocarcinoma.Additional markers(e.g.,GATA-3,CK20,CK34βE12)aid in differential diagnosis,though individual markers lack specificity.Comprehensive evaluation integrating clinical presentation,imaging,and clinicopathological features is essential for accurate diagnosis.
10.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.


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