1.Research progress on the mechanisms of oxidative stress in retinopathy of prematurity
Na LI ; Yirong QIN ; Yi ZHU ; Ribo PENG
International Eye Science 2026;26(1):45-49
Retinopathy of prematurity(ROP)is a leading cause of childhood blindness, with extremely preterm and very-low-birth-weight infants now constituting the main high-risk group. ROP progresses in two stages: early retinal microvascular degeneration and progressive vascular arrest, followed by abnormal neovascularization in the avascular area. Early oxidative and nitrosative stress—amplified by oxygen fluctuations and immature antioxidant defenses—drives the two-phase pathogenesis via hypoxia-inducible factor/vascular endothelial growth factor(HIF/VEGF), NOX/STAT3, and nuclear factor erythroid 2 related factor 2(Nrf2)-antioxidant response element(ARE)pathways, mediating apoptosis of endothelial cells, damage to barrier and pathological angiogenesis. This review systematically analyzes different oxygen-induced retinopathy(OIR)models, elucidates key signaling pathways including Notch, Wnt in physiological and pathological vascularization, with particular emphasis on the biphasic effects of Nrf2 and the differential roles of NOX signaling between phases. We also discuss the limitations of anti-VEGF therapy and oxygen management principles. Reactive oxygen species(ROS)play context-dependent roles across vaso-obliteration and neovascularization phases. Based on mechanistic insights, we propose future directions including combined/sequential interventions, ferroptosis and lipid peroxidation targeting, nano-delivery systems for enhanced bioavailability, and perinatal safety assessment strategies, aiming to provide translatable mechanistic basis for reducing pathological neovascularization while promoting physiological vascular development.
2.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; 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(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
3.Characteristics of peripheral blood lymphocyte subsets in children with mycoplasma pneumoniae pneumonia under different infection states
Jin LI ; Guangzheng ZHUO ; Shuang GUO ; Gui YANG ; Yunbao PAN ; Yirong LI
Chinese Journal of Preventive Medicine 2025;59(3):344-351
The research investigated the characteristics of lymphocyte subsets in peripheral blood of children with mycoplasma pneumoniae pneumonia in different infection states. The retrospective cross-sectional study selected 194 children with pneumonia from October 2023 to January 2024 in Zhongnan Hospital of Wuhan University as the study objects, patients aged 7 months to 13 years old, including 91 female children and 103 male children. According to the types of pathogens, the children with pneumonia were divided into single MP infection group (80 cases), non-MP infection group (29 cases) and mixed pathogen infection group (85 cases). According to the mutation of MP23S rRNA gene, the MPP children were divided into drug-resistance group (112 cases) and non-drug-resistance group (53 cases). According to the results of bronchoscopy and imaging, the MPP children were divided into severe group (35 cases) and mild group (130 cases). Pathogen infection, the percentage and absolute count of lymphocyte subsets in peripheral blood, hypersensitive CRP, interferon-γ, tumor necrosis factor-α, interleukin-10, interleukin-4, interleukin-6 and interleukin-2 in each group were analyzed retrospectively. The levels of the test items in each group were compared. The value of peripheral blood lymphocyte subsets in the diagnosis of MPP in children was evaluated by ROC curve. The results showed that the co-infection rate of MPP children was 51.51% (85/165). Streptococcus pneumoniae was the most common co-infection (39/85, 45.88%), followed by Haemophilus influenzae (26/85, 30.89%). The mutation rate of MP resistance gene was 67.88% (112/165) in MPP children tested for tNGS in bronchoalveolar lavage fluid. The absolute counts (cells/μl) of CD3 +, CD3 +CD4 +, CD3 +CD8 +, CD3 -CD19 +, CD3 -CD16 +CD56 +and CD3 +CD16 +CD56 + in the simple MP group (1 164, 612, 415, 242, 168, 50) and the mixed pathogen group (1 285, 694, 457, 313, 176, 52) were significantly lower than those in the non-MP group (2 092, 1 037, 660, 541, 295, 86) ( P<0.05). There was no significant difference between drug-resistant group and non-drug-resistant group ( P>0.05). The CD3 +CD4 +% (34.91) and the absolute counts of CD3 -CD16 +CD56 + (148 cells/μl) in severe group was significantly lower than that in mild group (37.91, 187 cells/μl), and CD3 -CD19 +% (19.48) was significantly higher than that in mild group (16.33) ( P<0.05). The median values (cells/μl) of CD3 + (1 093, 925), CD3 +CD4 + (576, 543), CD3 +CD8 + (401, 356), CD3 -CD19 + (238, 234) and CD3 -CD16 +CD56 + (181, 153) in MPP children aged 4 to 8 years and 9 to 12 years were lower than the reference range in corresponding age. ROC curve analysis showed that the AUC of peripheral blood lymphocyte subsets for MPP diagnosis was 0.813, and the sensitivity was 79.3%, the specificity was 75%. In conclusion, the co-infection rate of MPP children was higher than single MP infection. The characteristics of peripheral blood lymphocyte subsets in children with pneumonia were that the absolute count test value of MPP children was significantly lower than that of non-MP infection, and there are differences between MPP children clinical types.
4.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.
5.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.
6.Algorithm for brain MRI tumor detection based on improved YOLOv7
Jingyi BAI ; Yirong WU ; Xiaolong LI ; Shuifa SUN
Chinese Journal of Medical Physics 2025;42(3):336-346
Brain MRI data is characterized by large volumes and susceptibility to noise and artifacts,which pose significant challenges of improving the speed and accuracy of brain tumor detection and analysis due to the tumors'diverse types,shapes,and boundaries that are both similar and highly variable.Therefore,a series of improvements based on YOLOv7 algorithm are proposed for enhancing detection precision and speed:(1)employing partial convolution during feature extraction to reduce the model's parameters and improve overall detection speed;(2)in light of the complex variability of brain tumors,introducing a three-dimensional spatial attention mechanism during feature extraction to enhance the model's focus on critical image features;(3)replacing the original IoU loss function with WIoU to increase the attention to medium-quality anchor boxes during bounding box regression for further improving detection accuracy.Experiments conducted on two public brain tumor datasets,Brain_Tumor and Glioma_of_test,show that the improved model achieves mAP of 96.9%and 92.8%,which are 1.4%and 2.4%higher than the original YOLOv7 model,and the frames per second reach 162.7 and 158.1,showing improvements of 6.4 and 18.2,respectively.These enhancements enable more effective detection of brain tumors in MRI images.
7.DHLX studied correlation between regulation of biliary flora and inflammatory factors on gallbladder stone formation
Yirong GAN ; Yuan YU ; Jinmei CHEN ; Chengji LI ; Wen YANG ; Jiaoan PANG ; Chunli LIU ; Lijun XIAO ; Jinhao TENG
Chinese Journal of Immunology 2025;41(3):644-649
Objective:By sequencing and analyzing the biliary flora by 16S rDNA high-throughput sequencing technology,to identify the main flora associated with gallbladder stone formation and the main flora regulated by the Dahuang lingxian(DHLX),pre-liminary investigation the effect of DHLX on the biliary flora.Methods:The 50 male guinea pigs were randomly divided into Normal group,Model group,DHLX group.There were 15 guinea pigs in the normal group and 20 guinea pigs in the DHLX group,and 20 guin-ea pigs in the model group:the guinea pig model of gallstone was replicated with high-fat lithogenic diet,which was simultaneously ad-ministrated by gavage.After continuous intervention for 8 weeks,bile and gallbladder tissue samples were collected,and the gallstone formation rate of guinea pigs in each group was calculated,the pathological morphological changes of gallbladder tissue were detected by HE,T-CHO,TBA,LPS,IL-6,TNF-α were detected by ELISA,and the changes of biliary flora were detected by 16S rDNA;the correlation between biliary flora and bile index was detected by Pearson statistical method.Results:The stone formation rate of guinea pigs in the normal group was 8.3%,the rate of model stone composition was 90.8%,and the stone composition rate of DHLX group was 36.4%,and the HE staining results showed that compared with the normal group,the mucous membrane of the guinea pig in the model group was thickened,the columnar epithelial cells were arranged in a large number of inflammatory cells,and the columnar epi-thelial cells of the gallbladder mucosa in the chinese medicine group were arranged neatly compared with the model group,the thick-ness of the mucosa was reduced compared with the model group,and some inflammatory cells were infiltrated;ELISA results showed that compared with the normal group,the expressions of T-CHO,LPS,IL-6 and TNF-α in the bile of guinea pigs in the model group were significantly increased(P<0.01),while the content of TBA was significantly reduced(P<0.01);compared with the model group,the expression of LPS and IL-6 in the bile of the DHLX group were significantly reduced(P<0.01).The results of 16S rDNA showed that compared with the normal group the Ace index and Chao1 index of the model group were significantly reduced(P<0.01),and the Chao1 index of the DHLX group was significantly higher than that of the model group(P<0.05);biliary flora at the genera level was mainly composed of Burkholderia,Sphingomycetes,Breghamus,Delfortella,Pseudomonas;correlation analysis showed that total cholesterol was negatively correlated with the abundance of Methyloversatilis(P<0.05),and total bile acids were positively corre-lated with the abundance of Burkholderia(P<0.05),and Pseudomonas erythrocytes,Rhizobia,the abundance of Phreatobacter was negatively correlated(P<0.01)and LPS was positively correlated with the abundance of Pseudomonas erythrocytes(P<0.01).Conclu-sion:Biliary microflora disorder exists in the formation of biliary stones,and biliary microflora may participate in the formation of stones by regulating cholesterol,bile acids and LPS.DHLX can regulate the changes in the abundance of the microflora,make the structure of the microflora become normal,reduce the inflammation of the gallbladder,and prevent the formation of gallstones.
8.Establishment of a nursing quality evaluation indicator system for pulse indicator continuous cardiac output monitoring
Yirong ZHU ; Lizhu WANG ; Qian LI ; Junfeng HE ; Xiaodan LU ; Yan XIANG ; Meijuan LAN
Chinese Journal of Practical Nursing 2025;41(4):267-274
Objective:To construct a nursing quality evaluation indicator system for pulse indicator continuous cardiac output (PiCCO) monitoring and provide a basis for evaluating the nursing quality of PiCCO monitoring.Methods:Using Donabedian′s "structure-process-result" three-dimensional quality evaluation model as the theoretical framework, the nursing quality evaluation indicator system for PiCCO was established through literature search, Delphi expert correspondence, and hierarchical analysis during the period May to August 2023.Results:Of the 22 experts, 6 were male and 16 were female, aged (46.59 ± 4.34) years. The return rates of the questionnaires of the 2 rounds of expert correspondence were both 100%, the coefficients of expert authority were both 0.945, and the Kendall coordination coefficients were 0.045-0.186 ( χ2 values were 2.00-221.46, all P<0.05) and 0.045-0.132 ( χ2 values were 2.00-82.16, all P<0.05), respectively. The finalized nursing quality evaluation indicator system for PiCCO included 3 primary indicators, 7 secondary indicators, and 36 tertiary indicators. Conclusions:The nursing quality evaluation indicator system for PiCCO is practical and scientific, which can provide reference for PiCCO monitoring nursing quality evaluation.
9.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
10.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.

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