1.Predictive value of high-sensitivity cardiac troponin T for death in old patients with stable coronary heart disease
Shaojing ZHANG ; Qing WANG ; Linlin FU ; Yunjing CUI ; Xueliang ZHAI
Chinese Journal of Geriatric Heart Brain and Vessel Diseases 2025;27(7):881-884
Objective To investigate the value of hs-cTnT in predicting all-cause death in the elderly with SCAD.Methods A prospective cohort observation study was conducted on 274 old adults with SCAD hospitalized in our department from January 2016 to January 2019.Their hs-cTnT level was measured,and according to the results,they were divided into lower(≤13.0 ng/L,94 cases),middle(14.0-22.0 ng/L,94 cases)and upper(≥23.0 ng/L,86 cases)tertile groups.The general clinical data were compared among the three groups.Kaplan-Meier survival curve was drawn to analyze the survival differences among groups.Cox proportional hazards regression analysis was applied to identify risk factors for mortality.ROC curve analysis was applied to evaluate the predictive value of hs-cTnT for all-cause mortality.Results During a me-dian follow-up period of 32 months,62(22.63%)patients died among the 274 patients,account-ing for 75.8%dying of non-cardiovascular diseases.There were statistically differences in the three tertile groups in terms of age,male ratio,proportions of hypertension,chronic obstructive pulmonary disease and chronic kidney disease,number of comorbidities,estimated glomerular fil-tration rate,albumin and hemoglobin levels,left ventricular ejection fraction,left ventricular mass index,and mortality rate(P<0.05,P<0.01).COX proportional hazards regression model showed the upper tertile group had significantly lower cumulative survival rate than the middle and lower tertile groups(Plog rank<0.01).Multivariate Cox proportional hazards regression analysis indicated that hs-cTnT≥23.0 ng/L level was still a risk factor for death in both model 2(HR=3.749,95%CI:1.703-8.256,P=0.001)and model 3(HR=2.990,95%CI:1.358-6.581,P=0.007).ROC curve analysis revealed that the AUC value of hs-cTnT level in predicting death was 0.736,with a cut-off value of 25 ng/L.Conclusion For elderly SCAD patients,despite the existence of multiple comorbidities and the priority of non-cardiovascular death,hs-cTnT,a marker reflecting myocar-dial injury,is still a predictor for risk of death in the population.
2.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.
3.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.
4.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.
5.Analysis of karyotype results and clinical significance of amniotic fluid of 2 725 cases in southern Anhui from 2017 to 2023
Yuping WANG ; Xia FU ; Yuanyuan NING ; Qin LI ; Qing CHEN ; Qiwen WU
Journal of Shenyang Medical College 2025;27(2):135-140
Objective:To investigate the distribution and clinical significance of amniotic fluid karyotype results in 2 725 cases from southern Anhui.Methods:The karyotypes of amniotic fluid from 2 725 cases of second-trimester pregnant women treated in our hospital from Jan 2017 to Dec 2023 were collected.The annual abnormal detection rate and overall abnormal rate were analyzed.Meanwhile,the abnormal detection rate was compared among 8 groups of different clinical indication including adverse pregnancy history,advanced maternal age(≥35 years),high risk of Down syndrome screening,high risk of non-invasive prenatal testing(NIPT),nuchal translucency thickness(NT)≥2.5 mm,abnormal ultrasound findings,two or more concurrent positive indications,and others.The abnormal detection rate was calculated within high risk of Down syndrome screening and NIPT.Results:Significant differences in annual abnormal rates were observed from 2017 to 2023(χ2=19.705,P=0.003).Among 2 725 cases,233(8.55%)showed abnormal karyotypes.Among them,abnormal autosomal number was the most prevalent(4.41%,120/2 725),with inversion being the most common chromosome structural abnormality.Significant differences in abnormal rates were noted among the eight clinical indication groups(χ2=438.516,P<0.01).No statistical difference was found in abnormal detection rates among the three high-risk subgroups of Down syndrome screening(χ2=0.323,P=0.851),while significant differences were observed within the high-risk subgroups of NIPT(χ2=100.901,P<0.01).Polymorphisms were detected in 65 cases(2.38%).Conclusions:Chromosomal numerical and structural abnormalities have been detected in southern Anhui over the past seven years,with variations across subgroups.Karyotype analysis effectively detects second-trimester fetal chromosomal abnormalities,aiding in the prevention of birth defects and worthing clinical application.
6.Healthcare institution resilience and the influencing factors during infectious disease outbreaks
Yaqun FU ; Jiawei ZHANG ; Bing HAN ; Quan WANG ; Zheng ZHU ; Zhijie NIE ; Yiyang TAN ; Qing LIU ; Xiaoguang LI ; Jing GUO ; Rongmeng JIANG ; Li YANG
Journal of Peking University(Health Sciences) 2025;57(3):529-536
Objective:To analyze the association between healthcare workers mental health,institu-tional supplies and facilities,inter-organizational coordination during infectious disease outbreaks,and the healthcare institution resilience.Methods:An online questionnaire survey was conducted among the healthcare workforce from 146 institutions in Beijing from January 13,2023 to February 9,2023,and a total of 1 434 eligible respondents were included.The sample comprised 408 responses from tertiary hos-pitals,117 from secondary hospitals,and 909 from primary care institutions.The resilience indicator for healthcare institutions was defined as the degree to which medical services met patient demands,with in-fluencing factors including physical factors,such as material shortages and facility space adaptation or ex-pansion,organizational factors such as information sharing and patient referral,and psychological factors were evaluated using job satisfaction(extrinsic satisfaction,intrinsic satisfaction),burnout(emotional exhaustion,depersonalization,reduced personal accomplishment),and depression status.Ordered mul-ticlassification Logistic regression was used to examine the impact of various factors on the degree to which healthcare services met patient needs;additionally,demographic factors that might influence institutional resilience were controlled.Results:During the emergency response phase,93%of hospitals maintained the capacity to meet patient needs,though tertiary hospitals demonstrated significantly higher rates of service inadequacy(21.05%).Material shortages were reported across all institutions,with tertiary hos-pitals experiencing more frequent multi-item shortages.Inter-institutional collaboration patterns revealed substantial variation:87.50%of primary care facilities,42.86%of secondary hospitals,and 31.58%of tertiary hospitals.Healthcare workers across all levels reported mild depressive symptoms and moderate-to-severe burnout levels.Regression analysis showed high satisfaction(overall satisfaction β=0.04,ex-trinsic satisfaction β=0.06,and intrinsic satisfaction β=0.08),low degree of job burnout(emotional exhaustion β=-0.04,depersonalization β=-0.07 and reduced personal accomplishment β=0.01),low degree of depression(β=-0.06)were significantly associated with higher healthcare institution re-silience.In addition,material shortages were significantly associated with lower resilience,and renova-tion and expansion of treatment spaces,and information sharing,were all associated with higher resilience.Demographic factors(age,gender,marital status,educational background,etc.)had no sig-nificant impact on resilience.Conclusion:Mental health status significantly influences healthcare institu-tion resilience.As human resources constitute the core asset of healthcare institutions,strategic optimiza-tion of workforce allocation and psychological support interventions can effectively strengthen resilience.Moreover,healthcare institution resilience is positively impacted by orderly material supply chains,timely resource distribution,and adaptive reconfiguration of clinical spaces.Finally,facilitating information sharing also enhances institutional resilience.
7.Mechanism of cofilin in regulating prostate cancer progression and potential therapeutic strategies
Fang-zhi FU ; Li-tong WU ; En-min FENG ; Xiang ZHAO ; Neng WANG ; Biao WANG ; Qing ZHOU
Chinese Pharmacological Bulletin 2025;41(7):1206-1211
The molecular mechanisms underlying the develop-ment and metastasis of prostate cancer remain elusive.This comprehensive review delves into the intricate role of cofilin,an actin-binding protein,in the pathogenesis and progression of prostate cancer.Cofilin is a significant protein in cytoskeletal dynamics,and any dysregulation may result in the morphological changes in normal cells and the invasion and metastasis of tumor cells.Research has revealed that the activity of cofilin is regula-ted by various mechanisms,including phosphorylation/dephos-phorylation and interactions with other molecules.Moreover,this review discusses promising therapeutic interventions,such as co-filin inhibitors and gene therapy,which have demonstrated effica-cy in preclinical models.The challenge of clinically preventing the transition to castration-resistant prostate cancer and tumor metastasis is widely recognized,necessitating the development of precise drug treatments and biomarker identification.As a key regulatory protein,cofilin provides a more comprehensive refer-ence for the prevention and treatment of prostate diseases.
8.Icariin improves injury of tight junctional function by regulating balance of mTORC1 and mTORC2 in testicular Sertoli cells in naturally aging mice
Yao-ting CHENG ; Chang-cheng ZHANG ; Guo-qing FU ; Tan WANG ; Jian-min MAO ; Jian-ming SUN ; Hai-xia ZHAO
Chinese Pharmacological Bulletin 2025;41(6):1091-1098
Aim To explore the protective effect of icariin on the damage of tight junctional function of Sertoli cells in naturally aging mice and the related mechanism.Methods 15-month-old C57BL/6J male mice were randomly divided into three groups:aging model group,low-dose and high-dose icariin treatment group(5 and 20 mg·kg-1).Another 1-month-old C57BL/6J male mice were considered as adult control group(n=10).The mice in adult control group and aging model group were given the vehicle(0.5%sodi-um carboxymethyl cellulose solution)by intragastric administration,while the mice in icariin-treated groups were given different concentrations of icariin,respec-tively.After continuous administration of icariin for three months,the testes and epididymis were immedi-ately removed,weighed,and the organ index was calcu-lated.Sperm viability and sperm concentration in epi-didymis were measured.The morphological changes of testes were observed by HE staining.The ultrastructur-al changes of tight junctions of Sertoli cells were ob-served by transmission electron microscopy.The ex-pression levels of tight junction-related proteins ZO-1,Occludin,and Claudin11 of testicular Sertoli cells were detected by Western blot.The expression and localiza-tion of ZO-1,Occludin,Raptor,Rictor,p-70S6K,and p-rps6 were detected by immunofluorescence.Results Compared with the aging model group,icariin signifi-cantly increased testicular weight and its index,and ep-ididymal index,improved sperm viability and increased sperm concentration in naturally aging mice.In addi-tion,icariin improved the degeneration of testicular morphology and the damage of ultrastructure of Sertoli cell tight junction with aging.Furthermore,Western blot results showed that icariin up-regulated the expres-sion of ZO-1 and Occludin,but had no significant effect on the expression of Claudin 11.Immunofluorescence assay showed that icariin up-regulated the expression of Rictor,and down-regulated the expression of p-70S6K,p-rps6 and Raptor.Conclusions Icariin improves the tight junction damage of Sertoli cells in naturally aging mice,and its mechanism may be related to restoring the balance between mTORC1 and mTORC2.
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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