1. Research on the dynamic changes of neurological dysfunction and cognitive function impairment in traumatic brain injury
Cheng-Gong ZOU ; Hao FENG ; Bing CHEN ; Hui TANG ; Chuan SHAO ; Mou SUN ; Rong YANG ; Jia-Quan HE
Acta Anatomica Sinica 2024;55(1):43-48
Objective To explore the dynamic changes and mechanisms of neurological and cognitive functions in mice with traumatic brain injury (TBI). Methods Totally 60 12⁃month⁃old Balb/ c mice were divided into control group (10 in group) and TBI group (50 in group). TBT model mice were divided into 5 subgroups according to the time of model construction, including model 1 day, model 1 day, model 3 day, model 7 day, model 14 days and model 28 days group with 10 in each group. At the 29th day of the experiment, neurological scores and step down tests were carried out. After the test, the mice were sacrificed for brains which were detected by immunohistochemistry staining, inflammatory cytokine tests and Western blotting. Results Compared with the control group, the neurological scores of mice in TBI group increased, and then decreased after the 7th day when the scores reached the peak. However, the latency of step down errors was lower than control group, and the number of step down errors was higher than control group which had no changes. Compared with the control group, the expression of lonized calcium⁃binding adapter molecule 1(IBA1), chemokine C⁃X3⁃C⁃motif ligand1 (CX3CL1), C⁃X3⁃C chemokine receptor 1(CX3CR1), NOD⁃like receptor thermal protein domain associated protein 3 (NLRP3), and phosphorylation nuclear factor(p⁃NF)⁃κB in TBI group increased and reached to the peak at the 7th day, and then started to decrease. At the same time, the levels of inflammatory cytokines interleukin⁃6(IL⁃6) and tumor necrosis factor⁃α(TNF⁃α) first increased to the peak, and then began to decrease. However, compared with the control group, the expression of amyloid β(Aβ) protein and p⁃Tau protein in the model group continued to increase at all time. Conclusion The TBI model caused continuous activation of microglia along with inflammatory response, which first increased and then decreased, resultsing in neurological scores changes. In addition, the inflammatory response may act as a promoter of Aβ protein deposition and Tau protein phosphorylation, leading to cognitive impairment in mice.
2.Clinical trial of Morinda officinalis oligosaccharides in the continuation treatment of adults with mild and moderate depression
Shu-Zhe ZHOU ; Zu-Cheng HAN ; Xiu-Zhen WANG ; Yan-Qing CHEN ; Ya-Ling HU ; Xue-Qin YU ; Bin-Hong WANG ; Guo-Zhen FAN ; Hong SANG ; Ying HAI ; Zhi-Jie JIA ; Zhan-Min WANG ; Yan WEI ; Jian-Guo ZHU ; Xue-Qin SONG ; Zhi-Dong LIU ; Li KUANG ; Hong-Ming WANG ; Feng TIAN ; Yu-Xin LI ; Ling ZHANG ; Hai LIN ; Bin WU ; Chao-Ying WANG ; Chang LIU ; Jia-Fan SUN ; Shao-Xiao YAN ; Jun LIU ; Shou-Fu XIE ; Mao-Sheng FANG ; Wei-Feng MI ; Hong-Yan ZHANG
The Chinese Journal of Clinical Pharmacology 2024;40(6):815-819
Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P<0.05).After continuation treatment,the remission rate was 54.59%(202 cases/370 cases),and the recurrence rate was 6.49%(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35%(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.
3.Bioequivalence study of ritonavir tablets in Chinese healthy subjects
Yuan-Yuan XU ; Chuan-Shu WANG ; Shao-Chun CHEN ; Jia-Xiang DING ; Xue-Feng WANG ; He-Yue WANG ; Jing XIE ; Huan ZHOU
The Chinese Journal of Clinical Pharmacology 2024;40(10):1502-1506
Objective To evaluate the bioequivalence of a single oral dose of ritonavir in fasted and fed conditions in healthy Chinese adult subjects with the test and reference formulations.Methods A single-center,open-label,randomized,single-dose,two-periods,two-sequence crossover design was used,and 64 subjects were enrolled in both the fasted and fed groups.The subjects received 100 mg of the test preparation or reference preparation orally per cycle,and the drug concentration of ritonavir in plasma was detected using the high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS)method.Pharmacokinetic parameters were estimated by a non-compartment model,and SAS 9.4 software was used for statistical analysis.Results Arithmetic mean values of the main pharmacokinetic parameters of the subject formulation of ritonavir tablets and the reference formulation in the fasting group:Cmax were(791.90±400.20)and(809.60±449.14)ng·mL-1;AUC0_t were(6 072.61±2 631.98)and(6 296.30±3 388.95)ng·h·mL-1;AUC0-∞ were(6 129.59±2 655.57)and(6 347.26±3 434.12)ng·h·mL-1,respectively.Arithmetic mean values of the main pharmacokinetic parameters of the subject formulation of ritonavir tablets and the reference formulation in the fed group:Cmax were(512.37±233.60)and(521.74±223.87)ng·mL-1;AUC0_t were(4 203.43±2 221.33)and(4 200.13±1 993.50)ng·h·mL-1;AUC0_∞ were(4 259.21±2 266.88)and(4 259.63±2 044.12)ng·h·mL-1.The 90%confidence intervals for the geometric mean ratios of Cmax,AUC0_t and AUC0_∞ of the prototype drug ritonavir in plasma after oral administration of 100 mg of the test and reference formulations of ritonavir tablets under fasting and fed conditions fell within the 80.00%to 125.00%equivalence interval.Conclusion The test and reference formulations of ritonavir tablets were bioequivalent under fasting and postprandial conditions.
4.Association between unhealthy lifestyles and hypertension, diabetes and dyslipidemia in old adults in China
Tingting YE ; Ying SHAO ; Bin YU ; Changwei CAI ; Chuanteng FENG ; Peng JIA ; Shujuan YANG
Chinese Journal of Epidemiology 2024;45(3):385-392
Objective:To analyze the individual and cumulative effects of unhealthy lifestyle on the prevalence of hypertension, diabetes and dyslipidemia in old adults in China, and find out the critical lifestyle in the network.Methods:Based on the baseline data of Yunnan Behavior and Disease Surveillance Cohort in 2021, a total of 16 763 older adults aged ≥60 years were included in our study. The unhealthy lifestyle factors including smoking, drinking, unhealthy eating habit, lower physical activity level, abnormal BMI and abnormal waist circumference. We calculated the unhealthy lifestyle score by using the cumulative exposures of each participant. Multiple logistic regression and mixed graphical models were used to describe the association between unhealthy lifestyle and the prevalence of hypertension, diabetes and dyslipidemia.Results:The prevalence of hypertension, diabetes and dyslipidemia were 57.0%, 11.5% and 37.0%, respectively. Most of the unhealthy lifestyles included in the study were risk factors for hypertension, diabetes and dyslipidemia, and the risks of disease increased with the increase of the unhealthy lifestyle score. The participants with the highest score (score: 6) had significantly higher prevalence of hypertension ( OR=3.99, 95% CI: 1.81-8.80), diabetes ( OR=4.64, 95% CI: 1.64-13.15) and dyslipidemia ( OR=4.26, 95% CI: 2.08-8.73) compared with those with lowest score (score: 0). In the network constructed by mixed graphical model, abnormal waist circumference (bridge strength=0.81) and hypertension (bridge strength=0.55) were vital bridge nodes connecting unhealthy lifestyle and hypertension, diabetes and dyslipidemia. Conclusions:The unhealthy lifestyle score was associated with risks for hypertension, diabetes and dyslipidemia. Abnormal waist circumference was the key factor for chronic diseases in old adults.
5.Analysis of factors associated with spread through air spaces(STAS) of small adenocarcinomas(≤2 cm) in peripheral stage ⅠA lungs and modeling of nomograms
Jing FENG ; Wei SHAO ; Xiayin CAO ; Jia LIU ; Jialei MING ; Ya’nan ZHANG ; Jianbing YIN ; Jin CHEN ; Honggang KE ; Lei CUI
Chinese Journal of Thoracic and Cardiovascular Surgery 2024;40(3):129-136
Objective:To investigate the relationship between spread through air spaces(STAS) of peripheral stage ⅠA small adenocarcinoma of the lung(≤2 cm) and related factors such as clinical and CT morphological features, and to construct a nomogram model.Methods:Relevant clinical, pathological and imaging data of patients who underwent lung surgery and were diagnosed as peripheral stage ⅠA small lung adenocarcinoma by postoperative pathology in the Affiliated Hospital of Nantong University from 2017 to 2022 were collected, of which cases that met the inclusion criteria from 2017 to 2021 served as the training group, and those that met the inclusion criteria in 2022 served as the validation group. The independent risk factors for the occurrence of STAS in peripheral stage ⅠA lung small adenocarcinoma were investigated by using univariate analysis and multifactorial logistic regression analysis, based on which a nomogram prediction model was constructed, and the subjects were analyzed by using the receiver operating characteristic curve( ROC), correction model, etc. were used to evaluate the model. Results:A total of 430 patients who met the criteria were included, including 351 patients in the training group(109 STAS-positive and 242 STAS-negative) and 79 patients in the validation group(23 STAS-positive and 56 STAS-negative). Univariate analysis showed that the patients in the two groups showed a significant difference in age(>58 years old), gender, smoking history, tumor location(subpleural, non-subpleural), pleural pull, nodule type, nodule maximal diameter, solid component maximal diameter, consolidation tumor ratio(CTR), lobulation sign, burr sign, bronchial truncation sign, vascular sign(includes thickening and distortion of blood vessels in/around the nodes), satellite lesions, and ground-glass band sign were statistically significant( P<0.05). The results of multifactorial logistic regression analysis showed that CTR( OR=4.98, P<0.001), lobulation sign( OR=4.07, P=0.013), burr sign( OR=3.66, P<0.001), and satellite lesions( OR=3.56, P=0.009) were the independent risk factors for the occurrence of STAS. Applying the above factors to construct the nomogram model and validate the model, the results showed that the ROC curve was plotted by the nomogram prediction model, and the area under the ROC curve( AUC) of the training set was 0.840(sensitivity 0.835, specificity 0.734), and the validation set had an AUC value of 0.852(sensitivity 0.786, specificity 0.783), and the training set and validation set calibration curves have good overlap with the ideal curve. Conclusion:CTR, lobular sign, burr sign, and satellite lesions are independent risk factors for STAS, and the nomogram model constructed in this study has good predictive value.
6.Influencing factors of hypertension and diabetes care cascade: a qualitative study
Zhenzhong WANG ; Xuejun YIN ; Jingsong YANG ; Jia LI ; Qinglan LIU ; Guoxi WEI ; Min CHEN ; Bin JING ; Ruitai SHAO ; Luzhao FENG
Chinese Journal of Preventive Medicine 2024;58(5):615-621
Objective:Employing the cascade care model, this qualitative study explores determinants influencing the cascading care stages of hypertension and diabetes by interviewing various stakeholders.Methods:In July 2023, purposive sampling was employed to recruit participants from Gongyi and Wugang cities in Henan Province, and Linqu County in Weifang City, Shandong Province. Semi-structured in-depth interviews were conducted with representatives of policymakers, healthcare institution managers, providers, and patients with hypertension and diabetes.And thematic analysis was performed using both inductive and deductive approaches.Results:A total of 82 individuals were interviewed, with an age range of (53.8±12.0) years, among which 48 (58.5%) were male; including 5 policymakers, 10 institutional managers, 20 healthcare providers, and 47 patients with hypertension and diabetes. The study identified both barriers and facilitating factors at the patient, healthcare provider, and system levels across various stages: awareness, screening, diagnosis, treatment, long-term management, and control of hypertension and diabetes.Conclusion:By delineating and analyzing the barriers and facilitators at each stage of hypertension and diabetes care, this study lays the groundwork for the development of effective, feasible, and sustainable implementation pathways, with significant implications for the enhanced management of hypertension and diabetes in China.
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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