1.Impact factor selection for non-fatal occupational injuries among manufacturing workers by LASSO regression
Yingheng XIAO ; Chunhua LU ; Juan QIAN ; Ying CHEN ; Yishuo GU ; Zeyun YANG ; Daozheng DING ; Liping LI ; Xiaojun ZHU
Journal of Environmental and Occupational Medicine 2025;42(2):133-139
Background As a pillar industry in China, the manufacturing sector has a high incidence of non-fatal occupational injuries. The factors influencing non-fatal occupational injuries in this industry are closely related at various levels, including individual, equipment, environment, and management, making the analysis of these influencing factors complex. Objective To identify influencing factors of non-fatal occupational injuries among manufacturing workers, providing a basis for targeted interventions and surveillance. Methods A total of
2.Distribution characteristics of self-reported diseases and occupational injuries among workers in manufacturing enterprises
Lin ZHANG ; Zhi’an LI ; Yishuo GU ; Juan QIAN ; Chunhua LU ; Jianjian QIAO ; Yong QIAN ; Zeyun YANG ; Xiaojun ZHU
Journal of Environmental and Occupational Medicine 2025;42(2):165-170
Background Diseases severely affect the efficiency of workers. Comorbidity refers to the coexistence of two or more chronic diseases or health problems in the same individual. Previous studies have primarily focused on occupational injuries caused by environmental exposures, while the analysis of the epidemiological characteristics of self-reported diseases and occupational injuries among manufacturing workers has been insufficient. Objective To analyze the distribution of self-reported diseases and occupational injuries among manufacturing workers, the strength of correlation between different diseases, and common disease combinations, and to preliminarily explore the relationship between self-reported diseases and occupational injuries. Methods A cross-sectional survey was conducted to investigate the occupational injuries of
3.Clinical features and variant spectrum of FGFR3-related disorders.
Shi-Li GU ; Ling-Wen YING ; Guo-Ying CHANG ; Xin LI ; Juan LI ; Yu DING ; Ru-En YAO ; Ting-Ting YU ; Xiu-Min WANG
Chinese Journal of Contemporary Pediatrics 2025;27(10):1259-1265
OBJECTIVES:
To study genotype-phenotype correlations in children with FGFR3 variants and to improve clinical recognition of related disorders.
METHODS:
Clinical data of 95 patients aged 0-18 years harboring FGFR3 variants, confirmed by whole‑exome sequencing at Shanghai Children's Medical Center from January 2012 to December 2023, were retrospectively reviewed. Detailed phenotypic characterization was performed for 22 patients with achondroplasia (ACH) and 10 with hypochondroplasia (HCH).
RESULTS:
Among the 95 patients, 52 (55%) had ACH, 24 (25%) had HCH, 9 (9%) had thanatophoric dysplasia, 3 (3%) had syndromic skeletal dysplasia, 2 (2%) had severe achondroplasia with developmental delay and acanthosis nigricans, and 5 (5%) remained unclassified. A previously unreported FGFR3 variant, c.1663G>T, was identified. All 22 ACH patients presented with disproportionate short stature accompanied by limb dysplasia, commonly with macrocephaly, a depressed nasal bridge, bowed legs, and frontal bossing; complications were present in 17 (77%). The 10 HCH patients predominantly exhibited disproportionate short stature with limb dysplasia and depressed nasal bridge.
CONCLUSIONS
ACH is the most frequent phenotype associated with FGFR3 variants, and missense variants constitute the predominant variant type. The degree of FGFR3 activation appears to correlate with the clinical severity of skeletal dysplasia.
Humans
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Receptor, Fibroblast Growth Factor, Type 3/genetics*
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Child
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Male
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Child, Preschool
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Female
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Infant
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Adolescent
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Dwarfism/genetics*
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Achondroplasia/genetics*
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Lordosis/genetics*
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Infant, Newborn
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Retrospective Studies
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Genetic Association Studies
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Bone and Bones/abnormalities*
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Phenotype
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Limb Deformities, Congenital
4.Characteristics of Gut Microbiota Changes and Their Relationship with Infectious Complications During Induction Chemotherapy in AML Patients.
Quan-Lei ZHANG ; Li-Li DONG ; Lin-Lin ZHANG ; Yu-Juan WU ; Meng LI ; Jian BO ; Li-Li WANG ; Yu JING ; Li-Ping DOU ; Dai-Hong LIU ; Zhen-Yang GU ; Chun-Ji GAO
Journal of Experimental Hematology 2025;33(3):738-744
OBJECTIVE:
To investigate the characteristics of gut microbiota changes in patients with acute myeloid leukemia (AML) undergoing induction chemotherapy and to explore the relationship between infectious complications and gut microbiota.
METHODS:
Fecal samples were collected from 37 newly diagnosed AML patients at four time points: before induction chemotherapy, during chemotherapy, during the neutropenic phase, and during the recovery phase. Metagenomic sequencing was used to analyze the dynamic changes in gut microbiota. Correlation analyses were conducted to assess the relationship between changes in gut microbiota and the occurrence of infectious complications.
RESULTS:
During chemotherapy, the gut microbiota α-diversity (Shannon index) of AML patients exhibited significant fluctuations. Specifically, the diversity decreased significantly during induction chemotherapy, further declined during the neutropenic phase (P < 0.05, compared to baseline), and gradually recovered during the recovery phase, though not fully returning to baseline levels.The abundances of beneficial bacteria, such as Firmicutes and Bacteroidetes, gradually decreased during chemotherapy, whereas the abundances of opportunistic pathogens, including Enterococcus, Klebsiella, and Escherichia coli, progressively increased.Analysis of the dynamic changes in gut microbiota of seven patients with bloodstream infections revealed that the bloodstream infection pathogens could be detected in the gut microbiota of the corresponding patients, with their abundance gradually increasing during the course of infection. This finding suggests that bloodstream infections may be associated with opportunistic pathogens originating from the gut microbiota.Compared to non-infected patients, the baseline samples of infected patients showed a significantly lower relative abundance of Bacteroidetes (P < 0.05). Regression analysis indicated that Bacteroidetes abundance is an independent predictive factor for infectious complications (P < 0.05, OR =13.143).
CONCLUSION
During induction chemotherapy in AML patients, gut microbiota α-diversity fluctuates significantly, and the abundance of opportunistic pathogens increase, which may be associated with bloodstream infections. Patients with lower baseline Bacteroidetes abundance are more prone to infections, and its abundance can serve as an independent predictor of infectious complications.
Humans
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Gastrointestinal Microbiome
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Leukemia, Myeloid, Acute/microbiology*
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Induction Chemotherapy
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Feces/microbiology*
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Male
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Female
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Middle Aged
5.Investigation of the immune profile of multiple myeloma patients achieving long-term survival after autologous stem cell transplantation
Jingli GU ; Chuhang ZHONG ; Meilan CHEN ; Lifen KUANG ; Xiaozhe LI ; Beihui HUANG ; Junru LIU ; Juan LI
Chinese Journal of Internal Medicine 2024;63(4):365-370
Objective:To identify the characteristics of the bone marrow immune microenvironment associated with long-term survival in multiple myeloma (MM) patients.Methods:In the follow-up cohort of patients with newly diagnosed MM and who received “novel agent induction therapy and subsequent autologous stem cell transplantation and immunomodulator maintenance therapy” in the First Affiliated Hospital of Sun Yat-sen University, a cross-sectional study was carried out between August 2019 and May 2020. Using NanoString technology, the RNA expression of 770 bone marrow immune-related markers was compared between 16 patients who had progression-free survival ≥5 years and 5 patients with progressive disease. Among the 16 patients who achieved long-term survival, 9 achieved persistent minimal residual disease (MRD) negative while the other 7 had persistent positive MRD. The functional scores of each kind of immune cells were calculated based on the expression level of characteristic genes, so as to indirectly obtained the proportion of each immune cell subset. The Mann-Whitney U test and the Kruskal Wallis test were used for statistical analysis. Results:The proportion of neutrophils was significantly higher in long-surviving MM patients than in patients with progressive disease [functional scores, 13.61 (13.33, 14.25) vs. 12.93 (12.58, 13.38); Z=2.31, P=0.021]. Among long-surviving patients, those who were MRD-positive had a significantly greater number of mast cells compared with those who were MRD-negative [functional scores, 7.09 (6.49, 8.57) vs. 6.03 (5.18, 6.69); H=2.18, P=0.029]. Compared with patients with progressive disease, four genes (CTSG, IFIT2, S100B, and CHIT1) were significantly downregulated and six (C4B, TNFRSF17, CD70, IRF4, C2, and GAGE1) were upregulated in long-surviving patients. Among long-surviving patients, only gene CMA1 was significantly upgraded, 10 genes (ISG15, OAS3, MX1, IFIT2, DDX58, SIGLEC1, CXCL10, IL1RN, SERPING and TNFSF10) were significantly downregulated in the MRD-positive group compared with that in the MRD-negative group, the first 5 of which are related to the interferon response pathway. Conclusions:The increased neutrophil and mast cell numbers may be related to long-term survival in MM. Interferon signaling activation may be a key bone marrow immune profiling feature for MRD-negative, long-surviving patients with MM.
6.Clinical trial of sacubitril/valsartan sodium on the patients with heart failure in acute myocardial infarction after PCI
Jie-Ting NIU ; Wen-Juan WANG ; Li ZHAO ; Liang-Liang ZUO ; Qian-Qian GU
The Chinese Journal of Clinical Pharmacology 2024;40(2):160-164
Objective To investigate the effect of sakubatrotril and valsartan in the treatment of heart failure after percutaneous coronary intervention(PCI)for acute myocardial infarction(AMI).Methods AMI patients who received PCI were randomly divided into treatment group and control group.Both groups were given routine basic treatment such as anti-platelet aggregation,lipidregulation,β-blocker and diuretic tolasemide,while the control group was given enalapril maleate tablet(5 mg,bid).The treatment group was given sacubactril valsartan sodium tablets(5 mg,bid)in addition to basic treatment.The clinical efficacy,myocardial injury markers,cardiac function,ventricular remodeling indexes,vascular endothelial function and cardiovascular adverse events(MACEs)were compared between the two groups.Results The treatment group and the control group were enrolled in 40 patients.After 3 months of treatment,the total effective rate of the treatment group was 95.00%and that of the control group was 80.00%.The difference between the total effective rate of the treatment group and the control group was statistically significant(P<0.05).After 3 months of treatment,the levels of creatine kinase isoenzyme(CK-MB)in treatment group and control group were(30.23±5.28)and(36.58±7.05)U·L-1,respectively;cardiac troponin Ⅰ(cTnⅠ)were(1.04±0.18)and(1.25±0.31)ng·mL-1,respectively;left ventricular ejection fraction(LVEF)were(40.29±6.32)%and(34.39±5.62)%,and endothelium-dependent diastolic function(FMD)were(15.72±2.83)%and(9.55±2.05)%,respectively;nitric oxide(NO)levels were(47.41±5.85)and(41.28±3.37)μmol·L-1;endothelin-1(ET-1)was(70.53±8.29)and(83.62±10.11)ng·L-1,respectively.Compared with the control group,the above indexes in treatment groups were statistically significant(all P<0.05).The incidence of MACEs was 10.00%in treatment group and 25.00%in control group,with no statistical significance(P>0.05).After 3 months of treatment,the incidence of adverse drug reactions in AMI patients in treatment group was 12.50%,and that in control group was 17.50%.There was no statistical significance in the incidence of adverse drug reactions in treatment group compared with control group(P>0.05).Conclusion Sacubactril valsartan can effectively prevent ventricular remodeling and improve vascular endothelial function in patients with heart failure after PCI.
7.Changing distribution and resistance profiles of common pathogens isolated from urine in the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yanming LI ; Mingxiang ZOU ; Wen'en LIU ; 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 ; 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 ; 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
Chinese Journal of Infection and Chemotherapy 2024;24(3):287-299
Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8%(62 219/261 893),and gram-negative bacteria 76.2%(199 674/261 893).The most common species were E.coli(46.7%),E.faecium(10.4%),K.pneumoniae(9.8%),E.faecalis(8.7%),P.mirabilis(3.5%),P.aeruginosa(3.4%),SS.agalactiae(2.6%),and E.cloacae(2.1%).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2%,52.8%and 37.0%,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7%,18.5%,16.4%,and 40.3%,respectively.Lower than 10%of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90%of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was<2%.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.
8.Changing resistance profiles of Enterococcus in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Na CHEN ; Ping JI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 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 2024;24(3):300-308
Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7%)and Enterococcus faecalis(41.5%).The strains were mainly isolated from urinary tract specimens(46.9%±2.6%),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6%).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1%and 1.3%,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7%in 2015 to 3.4%in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3%.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.
9.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.
10.Changing resistance profiles of Proteus,Morganella and Providencia in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yunmin XU ; Xiaoxue DONG ; Bin SHAN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Ping JI ; Fengbo ZHANG ; 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 ; 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 ; Hongyan ZHENG ; 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 2024;24(4):410-417
Objective To understand the changing distribution and antimicrobial resistance profiles of Proteus,Morganella and Providencia in hospitals across China from January 1,2015 to December 31,2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods Antimicrobial susceptibility testing was carried out following the unified CHINET protocol.The results were interpreted in accordance with the breakpoints in the 2021 Clinical & Laboratory Standards Institute(CLSI)M100(31 st Edition).Results A total of 32 433 Enterobacterales strains were isolated during the 7-year period,including 24 160 strains of Proteus,6 704 strains of Morganella,and 1 569 strains of Providencia.The overall number of these Enterobacterales isolates increased significantly over the 7-year period.The top 3 specimen source of these strains were urine,lower respiratory tract specimens,and wound secretions.Proteus,Morganella,and Providencia isolates showed lower resistance rates to amikacin,meropenem,cefoxitin,cefepime,cefoperazone-sulbactam,and piperacillin-tazobactam.For most of the antibiotics tested,less than 10%of the Proteus and Morganella strains were resistant,while less than 20%of the Providencia strains were resistant.The prevalence of carbapenem-resistant Enterobacterales(CRE)was 1.4%in Proteus isolates,1.9%in Morganella isolates,and 15.6%in Providencia isolates.Conclusions The overall number of clinical isolates of Proteus,Morganella and Providencia increased significantly in the 7-year period from 2015 to 2021.The prevalence of CRE strains also increased.More attention should be paid to antimicrobial resistance surveillance and rational antibiotic use so as to prevent the emergence and increase of antimicrobial resistance.

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