1.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
2.Bioinformatics and Animal Experiments Reveal Mechanism of Shouhui Tongbian Capsules in Treating Constipation
Yong LIANG ; Qimeng ZHANG ; Bin GE ; Yang ZHANG ; Yu SHI ; Yue LU ; Hongxi ZHANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(4):150-157
ObjectiveTo explore the mechanism of Shouhui Tongbian capsules in treating constipation based on the research foundation of its active components combined with network pharmacology and animal experiments. MethodsThe drug components were imported into SwissTargetPrediction to predict the targets of Shouhui Tongbian capsules, and constipation-related targets were collected from disease databases. A protein-protein interaction (PPI) network was constructed for the common targets shared by Shouhui Tongbian capsules and constipation to screen key targets, which was followed by gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses. A "bioactive component-target-pathway" network was constructed, and the core components of Shouhui Tongbian capsules in treating constipation were screened based on the topological parameters of this network. Molecular docking was employed to predict the binding affinity of core components to key targets. A mouse model of constipation was constructed to screen the key pathways and targets of the drug intervention in constipation. ResultsThe PPI network revealed six key constipation-related targets: protein kinase B (Akt1), B-cell lymphoma-2 (Bcl-2), glycogen synthase kinase-3β (GSK-3β), cyclooxygenase-2 (PTGS2), estrogen receptor 1 (ESR1), and epidermal growth factor receptor (EGFR). The KEGG pathway analysis showed that the phosphatidylinositol 3-kinase (PI3K)/Akt signaling pathway was the most enriched. The topological parameter analysis of the "bioactive component-target-pathway" network screened out the top 10 core components: auranetin, isosinensetin, naringin, diosmetin, quercetin, apigenin, luteolin, hesperidin, isorhapontigenin, and chrysophanol. Molecular docking results showed that the 10 core components had strong binding affinity with the 6 key targets. Animal experiments showed that after intervention with different doses of Shouhui Tongbian capsules, the time to the first black stool excretion was reduced and the fecal water content and small intestine charcoal propulsion rate of mice were improved. After treatment with Shouhui Tongbian capsules, the colonic mucosal injury and glandular arrangement were alleviated, and the muscle layer thickness was increased. Western blot results showed that Shouhui Tongbian capsules recovered the expression of apoptosis-related molecules mediated by the PI3K/Akt pathway in the colonic tissue of constipated mice. Terminal-deoxynucleotidyl transferase-mediated nick end labeling (TUNEL) results showed that the cell apoptosis rate of the colon significantly reduced after intervention with Shouhui Tongbian capsules. ConclusionThe results of network pharmacology and animal experiments confirmed that Shouhui Tongbian capsules can treat constipation through multiple targets and pathways. The capsules can effectively intervene in loperamide-induced constipation in mice by regulating the constipation indicators and reducing cell apoptosis in the colon tissue via activating the PI3K/Akt signaling pathway.
3.Efficacy comparison of foldable capsular body with scleral buckling in treating experimental retinal detachment
Yifan DONG ; Baike ZHANG ; Yong JIA ; Fan YANG ; Lisha GUO ; Xiangyang ZHANG ; Cong LU ; Zhonghao ZHANG ; Haiyan WU ; Xuemin TIAN
International Eye Science 2025;25(10):1566-1573
AIM: To compare the effectiveness of foldable capsular body(FCB)with traditional scleral buckling(SB)in the treatment of experimental retinal detachment animal models.METHODS: After successfully establishing rhegmatogenous retinal detachment(RRD)animal models, 24 New Zealand white rabbits were randomly divided into three groups(RRD models group, SB group, and FCB group), with 8 rabbits in each group. The FCB and SB groups underwent SB and FCB surgeries for the RRD animal models, while the RRD models group only consists of RRD models without any surgical intervention during the follow-up period. The follow-up duration was 3 mo. Wide-field neonatal fundus imaging system and ophthalmic B-ultrasound were used to assess the fundus conditions before and after surgery. The Icare® TONOVET Plus tonometer was utilized to evaluate intraocular pressure changes before and after surgery. The Eaton and Draize scoring systems were selected to monitor postoperative inflammatory reactions.RESULTS: The retinal reattachment rates in the FCB and SB groups were 87.5% and 75.0%, respectively, with no statistically significant difference between the groups(P>0.05). The intraocular pressure in both the FCB and SB groups increased postoperatively compared to preoperative levels(P<0.01), and there were no significant differences in intraocular pressure at any time points during the follow-up period between the groups(P>0.05). The intraocular pressure in the RRD models group remained at a low level throughout the follow-up period. The average surgical time for the FCB group was 16.87±2.29 min, which was shorter than 46.25±4.74 min in the SB group(t=-15.166, P<0.001). According to the Eaton and Draize scoring systems, the FCB group had lower grades of conjunctival hyperemia and edema in the early postoperative period compared to the SB group, indicating milder inflammatory reactions(P<0.05).CONCLUSION: Both FCB and SB are effective in treating experimental RRD. Compared to SB, FCB is simpler to operate, and also has a shorter surgical time and milder postoperative inflammatory reactions.
4.Evaluation of the weight loss effect of a comprehensive intervention among overweight and obese female college students
Chinese Journal of School Health 2025;46(11):1569-1573
Objective:
To investigate the weight loss effect of a comprehensive intervention model combining caloric restriction (CR), physical activity (PA), behavioral therapy (BT), breathing exercise (BE), and functional movement corrective training (FMCT)-referred to as the "CPBBF" model in overweight and obese female college students, so as to provide a reference for scientific weight loss interventions for college students.
Methods:
From March to May 2022, 46 overweight and obese female college students from Chongqing Water Resources and Electric Engineering College were recruited and randomly divided into an experimental group (24 participants) and a control group (22 participants). The control group received CR (prohibiting ad libitum snacking), PA in the first week, high intensity interval training (HIIT) for 30 s, and moderate intensity continuous training (MICT) for 1-5 min alternate 4 sets, duration 15-20 min. From the second week, adjust to HIIT and MICT alternating 3 min each for 5 sets, totaling 30 min, 4 times/week, 70 min/time and BT (60-90 min/session, 3 times/week). The experimental group incorporated FMCT (10-15 min of focused training per session, integrated with PA and daily life) and BE (advocating a gradual transition to proper breathing methods in daily life and low intensity training, 5 sessions/day, 10 min each). Body oxygen level test (BOLT), Functional Movement Screen (FMS), sports exercise attitude, and body composition indicators were measured at baseline (T0), after 12 weeks of intervention (T1), and after one year of follow up (T2). The differences were analyzed between groups through generalized estimation equations, and mixed effect model analysis was employed to explore predictive relationships among variables.
Results:
The results of the generalized estimation equation showed that time main effects of BOLT values, FMS scores, and exercise attitude among female college students were statistically significant ( Wald χ 2=18.75, 14.89, 12.45, all P <0.01); further intragroup comparisons revealed that BOLT, functional motor screening (FMS) scores, and physical exercise attitudeof female college students in the experimental group increased compared to T0, while the control group only showed an increase at T1 (all P <0.05). The group main effects for the aforementioned three indicators were statistically significant ( Wald χ 2=6.33, 5.21, 4.88), and the time by group interactions of BOLT values and FMS scores were also statistically significant ( Wald χ 2=4.56, 3.97) (all P <0.05). The time main effects of body weight, body mass index (BMI), and body fat ratio(BFR) in female college students were statistically significant ( Wald χ 2=44.27, 13.90, 82.33); further intragroup comparisons revealed that the experimental group of female college students showed a decrease in body weight, BMI and BFR at T1 and T2 compared to T0, while the control group only showed a decrease in these indicators at T1 (all P <0.05). The group main effects of weight and BFR were statistically significant ( Wald χ 2= 4.11 , 6.46), and the time by group interaction of BFR was statistically significant ( Wald χ 2=8.73) (all P <0.05).The results of mixed effect model analysis showed that BOLT ( β =1.52) and FMS ( β =1.81) could both positively predict physical exercise attitude, and physical exercise attitude had statistically significant negative predictive effects on weight, BMI, and BFR ( β =-0.08, -0.03 , -0.03) (all P <0.01).
Conclusion
The "CPBBF" comprehensive intervention effectively maintains weight loss effects by modulating the energy compensation mechanism with strong robustness.
5.A case of persistent atrial fibrillation treated with Marshall intravenous ethanol ablation with self-made perforated balloon combined with individualized ablation strategy
Ming-Yang TANG ; Bo LIU ; Wei CAI ; Xiao-Hua HUANG ; Lu-Yong HUANG ; Deng-Ke OU
Chinese Journal of Interventional Cardiology 2024;32(6):353-356
In the treatment of persistent atrial fibrillation with radiofrequency ablation,it is often necessary to add the ablation of external trigger foci of pulmonary vein on the basis of annular pulmonary vein isolation,including linear ablation,BOX ablation and fragmentation potential ablation.The isthmus of mitral valve is the most important component of linear ablation,but it is difficult to reach the isthmus of mitral valve for complete blockade by conventional radiofrequency ablation.The guide catheter was transported through the inferior vena cava to the coronary sinus,and the injection of Marshall vein anhydrous ethanol for ablation could achieve epicardial and myocardial block in the mitral isthmus,and the ablation combined with the endocardial patch ablation in the mitral isthmus could significantly improve the ablation effect,but there were disadvantages such as Marshall vein and coronary vein injury,high surgical cost and long time.This paper reports a case of persistent atrial fibrillation treated by self-made perforated balloon with Marshall intravenous anhydrous ethanol combined with individualized ablation strategy.No major adverse cardiovascular events or recurrence of atrial fibrillation occurred during 6 months of follow-up after discharge.
6.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; 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 ; Wei LI ; 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 ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
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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