1.Evaluation of the clinical value of electrophysiology of ocular surface in the diagnosis and treatment of blepharospasm in Meige syndrome
Gang LIU ; Qiangying GUO ; Jie XIANG ; Zhen XU ; Lili SHANG ; Yue ZHANG ; Xue YANG ; Meng LUO ; Qingqing ZHU ; Xianzhong LIU
Chinese Journal of Ocular Fundus Diseases 2025;41(6):428-434
Objective:To observe and assess the clinical value of electrophysiology of ocular surface in the diagnosis and treatment of blepharospasm in Meige syndrome (MS).Methods:A single-center, cross-sectional study. A total of 413 patients diagnosed with MS and undergoing surgical treatment at the Henan Provincial Meige Syndrome Diagnosis and Treatment Center of the Henan Provincial Third People′s Hospital from May 2022 to December 2023 were included as the MS group. A total of 110 age- and gender-matched spouses of patients and community volunteers were selected as the control group. The bioelectricity detection program of the electrooculogram was used; the frequency bandwidth was set at 0.3 to 300.0 Hz. Surface electrodes were employed to record the surface electrophysiological manifestations of the corrugator supercilii muscle and the lower orbicularis oculi muscle, as well as the conditions and temporal characteristics of spasm waves. Based on the amplitude and waveform of the electrophysiology of ocular surface signals, it can be classified into 0-4 grades. The blepharospasm was divided into conditionally induced type, spastic type, reverse spastic type, and oro-ocular elicited type. All patients were treated with neural circuit occlusion, and the postoperative follow-up time was 4.1 (0.5-19.0) months. The distribution of different grades of electrophysiology of ocular surface in the MS and control group at baseline were observed, as well as within the MS group at the last follow-up visit. Additionally, the blepharospasm grades in the MS group were also assessed. The comparison of the distribution of the number of eyes with different grades of electrophysiology of ocular surface between groups was conducted using the Mann-Whitney U test. Results:At baseline, in the MS group, the number of cases with corrugator supercilii muscle amplitudes and morphologies graded from 0 to 4 were as follows: 15 (3.60%, 15/413) for grade 0, 95 (23.00%, 95/413) for grade 1, 142 (34.38%, 142/413) for grade 2, 127 (30.75%, 127/413) for grade 3, and 34 (8.24%, 34/413) for grade 4. In the control group, the corresponding numbers of individuals were 82 (74.54%, 82/110) for grade 0, 24 (21.82%, 24/110) for grade 1, 4 (3.64%, 4/110) for grade 2, 0 (0.00%, 0/110) for grade 3, and 0 (0.00%, 0/110) for grade 4. For the orbicularis oculi muscle, there were 35 cases (8.47%) in grade 0, 124 cases (30.03%) in grade 1, 150 cases (36.32%) in grade 2, 90 cases (21.79%) in grade 3, and 14 cases (3.39%) in grade 4 in the MS group. In the control group, there were 86 cases (78.18%) in grade 0, 24 cases (21.82%) in grade 1, and 0 cases in grades 2, 3, and 4. There were statistically significant differences in the distribution of the number of eyes with different electrophysiology of ocular surface grading of the corrugator supercilii muscle and the orbicularis oculi muscle between the MS and control group ( Z=-14.51, -13.86; P<0.001). Meanwhile, there were statistically significant differences in the distribution of the number of eyes with different electrophysiology of ocular surface grading of the corrugator supercilii muscle and the orbicularis oculi muscle between preoperation and at the last follow-up in the MS group ( Z=-16.52, -17.36; P<0.001). In the MS group, there were 61 (14.77%, 61/413), 306 (74.09%, 306/413), 27 (6.54%, 27/413) and 19 (4.60%, 19/413) cases of blepharospasm conditionally induced type, spasm type, reverse spasm type and oro-ocular elicited type, respectively. Conclusion:The electrophysiology of the ocular surface can objectively reflect the activity of periocular neuromuscular.
2.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
3.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; 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 ; 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 ; 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 WEN ; 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(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
4.Investigating the correlation between white matter injury and cerebral perfusion in preterm infants using arterial spin labeling.
Xiang-Bo KONG ; Fan-Yue QIN ; Wen-Li DUAN ; Lin LU ; Xiao-Chan GUO ; Yan-Ran XUE ; Yin-Gang HONG ; Fa-Lin XU
Chinese Journal of Contemporary Pediatrics 2025;27(6):661-667
OBJECTIVES:
To explore the relationship between white matter injury (WMI) and cerebral perfusion in preterm infants using arterial spin labeling (ASL).
METHODS:
A total of 293 preterm infants (gestational age <34 weeks) hospitalized at the Third Affiliated Hospital of Zhengzhou University between June 2022 and June 2024 were included. After achieving clinical stability, the infants underwent brain magnetic resonance imaging (MRI) and ASL. Based on MRI findings, infants were classified into WMI (n=66) and non-WMI (n=227) groups. Cerebral perfusion parameters were compared between groups, and the association between WMI and perfusion alterations was evaluated.
RESULTS:
The WMI group showed a higher incidence of mild intraventricular hemorrhage (IVH) than the non-WMI group (P<0.05). Significantly lower cerebral perfusion was observed in the WMI group across bilateral frontal, temporal, parietal, and occipital lobes, as well as the basal ganglia and thalamus (P<0.05). After adjusting for gestational age, corrected gestational age at ASL scan, and mild IVH, WMI remained significantly associated with reduced regional perfusion (P<0.05).
CONCLUSIONS
WMI in preterm infants correlates with localized cerebral hypoperfusion. ASL-detected perfusion abnormalities may provide novel insights into WMI pathogenesis.
Humans
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White Matter/blood supply*
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Infant, Newborn
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Spin Labels
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Infant, Premature
;
Female
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Male
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Cerebrovascular Circulation
;
Magnetic Resonance Imaging
5.High expression of apolipoprotein C1 promotes proliferation and inhibits apoptosis of papillary thyroid carcinoma cells by activating the JAK2/STAT3 signaling pathway.
Yu BIN ; Ziwen LI ; Suwei ZUO ; Sinuo SUN ; Min LI ; Jiayin SONG ; Xu LIN ; Gang XUE ; Jingfang WU
Journal of Southern Medical University 2025;45(2):359-370
OBJECTIVES:
To investigate the expression of apolipoprotein C1 (APOC1) in papillary thyroid carcinoma (PTC) and its effects on proliferation and apoptosis of PTC cells.
METHODS:
The expression level of APOC1 in PTC and its impact on prognosis were analyzed using GEPIA 2 and Kaplan-Meier databases. Immunohistochemistry (IHC) and Western blotting were used to detect the expression of APOC1 in PTC and adjacent tissues and in 3 PTC cell lines and normal thyroid Nthyori 3-1 cells. In TPC-1 and BCPAP cells, the effect of Lipofectamine 2000-mediated transfection with APOC1 siRNA or an APOC1-overexpressing plasmid on cell growth and colony formation ability were examined by observing the growth curves and using colony-forming assay. The changes in cell cycle and apoptosis of the transfected cells were analyzed with flow cytometry. RT-qPCR and Western blotting were used to detect the changes in expressions of P21, P27, CDK4, cyclin D1, Bcl-2, Bax, caspase-3 and caspase-9 and the key proteins in the JAK2/STAT3 signaling pathway.
RESULTS:
APOC1 expression was significantly higher in PTC tissues and the 3 PTC cell lines than in the adjacent tissues and Nthyori 3-1 cells, respectively. In TPC-1 and BCPAP cells, APOC1 knockdown obviously reduced cell proliferative activity, increased the percentage of G0/G1 phase cells, lowered the percentages of S and G2 phase cells, promoted cell apoptosis, and downregulated mRNA and protein expression levels of CDK4, cyclin D1 and Bcl-2 and the protein levels of p-JAK2 and p-STAT3. APOC1 overexpression in the cells produced the opposite effects on cell proliferation, apoptosis, cell cycle and the mRNA and protein expressions. The application of AG490, a JAK2 inhibitor, strongly attenuated APOC1 overexpression-induced activation of the JAK2/STAT3 signaling pathway in BCPAP cells.
CONCLUSIONS
APOC1 overexpression promotes proliferation and inhibits apoptosis of PTC cells possibly by activating the JAK2/STAT3 signaling pathway and accelerating cell cycle progression.
Humans
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Apoptosis
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Cell Proliferation
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STAT3 Transcription Factor/metabolism*
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Signal Transduction
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Janus Kinase 2/metabolism*
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Thyroid Neoplasms/pathology*
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Thyroid Cancer, Papillary
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Cell Line, Tumor
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Carcinoma, Papillary
6.Expression and diagnostic value of CYBB and CSF1R in chronic rhinosinusitis with nasal polyps
Yu-Long MA ; Geng LI ; Jing-Fang WU ; Gang XUE ; Xu LIN
Medical Journal of Chinese People's Liberation Army 2025;50(1):35-43
Objective To analyze the gene expression characteristics of chronic rhinosinusitis with nasal polyps(CRSwNP)using bioinformatics methods,aim to investigate the potential biomarkers and their diagnostic value of CRSwNP.Methods(1)The CRSwNP Gene expression data set was downloaded from the American Gene Expression Omnibus(GEO)database.The differentially expressed genes(DEGs)between CRSwNP patients and healthy controls were screened through data analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis were performed on the identified DEGs.Protein-protein interaction(PPI)networks were constructed utilizing the STRING database,and the key genes were identified by using the cytoHubba plugin.The"Cibersort"package was used to analyze the influence of key genes on common immune cells.(2)Thirty-two patients diagnosed with CRSwNP in the First Affiliated Hospital of Hebei North University from June 2022 to June 2023 were selected as the CRSwNP group,and 21 patients with simple deviation of nasal septum without a history of sinusitis during the same period were selected as control group.The pathological characteristics of specimens in the two groups were examined using hematoxylin-eosin(HE)staining.Immunohistochemistry and Western blotting were used to detect the expression levels of key genes in CRSwNP.The levels of key proteins in plasma were detected using ELISA,and ROC curve was used to analyze its efficacy in diagnosing CRSwNP.Results(1)Analysis of three gene expression database sets(GSE36830,GSE23552,and GSE194282)showed that there were 156 DEGs in CRSwNP.GO functional enrichment and KEGG pathway analysis indicated that the functions of the above DEGs were mostly related to immune functions.Key genes such as cytochrome b-245 β chain(CYBB)and colony-stimulating factor 1 receptor(CSF1R)were identified.(2)The results of HE staining revealed that the epithelial of CRSwNP tissue was metaplastic into stratified squamous epithelium with interstitial edema.Both immunohistochemistry and Western blotting analyses indicated that the expression levels of CYBB and CSF1R in the CRSwNP group were significantly increased compared to control group(P<0.05).ELISA results demonstrated that CYBB[(21.20±3.00)μg/ml vs.(17.66±1.66)μg/ml,P<0.05]and CSF1[(477.37±86.63)pg/ml vs.(370.71±66.24)pg/ml,P<0.05]in CRSwNP group were significantly increased compare to control group.ROC curve analysis showed that plasma concentrations of CYBB and CSF1 had AUCs of 0.888(95%CI 0.802-0.974)and 0.821(95%CI 0.711-0.931)for diagnosing of CRSwNP,respectively;their combined AUC was 0.927(95%CI 0.851-1.000).Conclusions CYBB and CSF1R may be involved in the occurrence and development of CRSwNP.Plasma CYBB and CSF1 have high diagnostic value for CRSwNP.
7.Applied value of physical motor function assessment system in the risk assessment of recruit training injury
Wei WEI ; Wei-Xu ZHANG ; Lv-Gang ZHU ; Liang TANG ; Huan-Le LI ; Zhi-Chao XUE ; Liang ZHANG ; Hao-Feng WANG ; Qi CHANG
Medical Journal of Chinese People's Liberation Army 2025;50(5):531-535
Objective To assess the effectiveness of the evaluation of military physical function(EMPF)system in predicting the occurrence of military training injuries among new recruits to provide scientific guidance and methodological choice for military training.Methods A total of 527 new recruits from 5 grassroots units from July 2016 to February 2018 were selected for the study.The recruits underwent EMPF testing,and their military training injuries were monitored over a 2-year follow-up period.Those who sustained injuries during training were divided into injury group(n=163),while the remaining recruits were placed in healthy group(n=364).The predictive ability of the total EMPF score for training injuries was assessed using the receiver operating characteristic curve(ROC),and the correlation between the total EMPF score,individual test scores,and military training injuries were analyzed using binary logistic regression.Results The total EMPF score of new recruits in injury group(19.52±1.97)was significantly lower than that of healthy group(24.31±1.54)(P<0.001),which also demonstrated a high diagnostic value in predicting the risk of military training injuries,with an area under the curve(AUC)of ROC of 0.971(P<0.001).A cut-off value of 22 scores was found to have the highest accuracy in predicting future training injuries,with an odds ratio(OR)of 25.63,sensitivity of 0.939,specificity of 0.879,positive likelihood ratio of 7.76,and a post-test probability of 0.67.Binary logistic regression analysis revealed that 6 EMPF tests,including holding the ball over and leaning back,bending forward and touching the ground with the ball,lunge squat and twist,swallow balance with holding the ball afterward,vertical jump,and respiratory pattern assessment,were negatively associated with the risk of military training injuries(P<0.0001).Conclusion The EMPF system can effectively predict the risk of military training injuries,with military personnel whose total EMPF score is less than 22 being at higher risk of sustaining such injuries.
8.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.
9.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.
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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