1.Dosimetric comparison of the heart and its substructures between two hybrid radiotherapy plans following breast-conserving surgery for left-sided breast cancer
Lin GUO ; Hongrong REN ; Meng CHEN ; Chengjun WU ; Yun ZHOU ; Xiaobo RUAN ; Ji DING ; Weiyuan WU
Chinese Journal of Radiological Health 2025;34(2):174-178
Objective To compare the dosimetric differences in the heart and its substructures between two hybrid plans for hypofractionated whole-breast radiotherapy after breast-conserving surgery in patients with early-stage left-sided breast cancer. Methods A total of 46 patients with early-stage left-sided breast cancer who underwent hypofractionated whole-breast radiotherapy were randomly selected. Two hybrid radiotherapy plans were used, including hybrid intensity-modulated radiotherapy (H_IMRT) and hybrid volumetric-modulated arc therapy (H_VMAT). The heart and its substructures were contoured, including left anterior descending (LAD), left ventricle (LV), right coronary artery (RCA), and right ventricle (RV). The heart and substructure doses, as well as monitor units, were compared between H_IMRT and H_VMAT. Results Both hybrid plans met the clinical requirements. H_IMRT significantly outperformed H_VMAT for the heart (V10, V30, and Dmean), LAD (V30, V40, Dmax and Dmean), LV (V10, V20 and Dmean), RCA (Dmax, Dmean), and RV (V5, V10, Dmean) (P < 0.001). Additionally, H_IMRT was significantly superior to H_VMAT for heart V5, LAD V20, and RV V20 (P = 0.005, 0.035 and 0.037). For LAD (V15, V40) and LV (V5, V25), H_IMRT was slightly better than H_VMAT, and the difference was not statistically significant. Conclusion Both H_IMRT and H_VMAT hybrid radiotherapy plans are suitable for hypofractionated whole-breast radiotherapy after breast-conserving surgery in patients with early-stage left-sided breast cancer. H_IMRT is slightly better than H_VMAT in dose sparing for the heart and its substructures.
2.Research on the regulation of the MAPK signaling pathway by Suzi Jiangqi decoction to improve the inflammatory state of COPD patients
Xuxing YE ; Shuangshuang MA ; Lin SHENG ; Hui CHEN ; Xiaobo WANG
China Modern Doctor 2024;62(32):82-86,126
Objective To explore the impact of Suzi Jiangqi decoction(SJD)on the inflammatory state of patients with chronic obstructive pulmonary disease(COPD)through the regulation of the mitogen-activated protein kinase(MAPK)signaling pathway.Methods A total of 70 patients with stable COPD,treated from April 2023 to April 2024 at the Department of Traditional Chinese Medicine and Department of Respiratory outpatient clinic of Affiliated Jinhua Hospital,School of Medicine Zhejiang University were selected and randomly divided into observation group and control group,with 35 cases in each group.The control group received tiotropium bromide powder inhalation combined with budesonide/formoterol powder inhalation treatment,while the observation group was given SJD in addition to treatment of control group.After 12 weeks of treatment,the therapeutic effects were evaluated by assessing lung function,airway mucus hypersecretion,levels of interleukin(IL)-17,IL-6,and tumor necrosis factor(TNF)-α,CT quantitative parameters of the lung,as well as the expression levels of IL-17,p38MAPK,nuclear factor kappa-B(NF-κB)and C-X-C motif chemokine ligand 8(CXCL8)mRNA in sputum.Results Following treatment,there was a significant improvement in lung function indicators such as first second expiratory volume/forced vital capacity%,cough score,sputum difficulty score,sputum quality score,and sputum volume score for patients in both groups,with more pronounced improvements observed in observation group(P<0.05).The levels of serum cytokines IL-17,IL-6 and TNF-αdecreased in both groups after treatment,with observation group showing a more significant reduction(P<0.05).Additionally,the percentage ratio of low attenuation area to lung area(LAA%),emphysema index of lung CT in observation group significantly decreased after treatment(P<0.05).Similarly,the expression levels of IL-17,p38MAPK,NF-κB and CXCL8 mRNA in sputum were also significantly reduced after treatment in observation group(P<0.05).Conclusion SJD may improve lung function and inflammatory status in COPD patients by regulating the MAPK signaling pathway mediated by IL-17,demonstrating a positive therapeutic effect on the treatment of COPD.
3.Efficacy analysis of sacubitril/valsartan in the prevention and treatment of cardiac dys-function related to tumor therapy
Lin YITING ; Han QING ; Guo XIAOBO ; Zhang HONGMEI
Chinese Journal of Clinical Oncology 2024;51(4):186-191
Objective:To investigate the efficacy of sacubitril/valsartan in the treatment of cancer therapy-related cardiac dysfunction(CTRCD).Methods:A comprehensive analysis of all the literature on sacubitril/valsartan therapy for CTRCD published in Pubmed,Web of Science,Cochrane Library,Medline,and Embase from the inception of the database up to March 2023 was conducted,summarizing the tim-ing of drug administration,dosage,and efficacy,and further systematically summarizing the clinical studies on the use of the drug for the prevention of CTRCD.Results:After 3-12 months of treatment with sacubitril/valsartan for CTRCD,NYHA in cancer patients improved from grade Ⅱ-Ⅳ to grade Ⅰ-Ⅱ,LVEF increased by 3.0%to 37.0%,and NT-proBNP decreased by 280.0-65 498.0 pg/mL.Conclusions:The sacu-bitril/valsartan demonstrates efficacy in managing CTRCD and holds significant clinical utility in enhancing LVEF,GLS,and other patient indic-ators,thereby enabling the continuation of anti-tumor therapy and prolonging survival for cancer patients.
4.Dual-energy computed tomography assessment of monosodium urate load predicts gout flare risk—a prospective observational cohort study
Rui ZHOU ; Xiaobo AI ; Rongrong SUN ; Zhen LIU ; Xiaoou JIN ; Feng ZHANG ; Maichao LI ; Xiaomei XUE ; Changgui LI ; Lin HAN
Chinese Journal of Endocrinology and Metabolism 2024;40(7):573-579
Objective:To investigate whether dual-energy computed tomography(DECT) measurement of monosodium urate(MSU) crystal loading can predict the risk of gout flares.Methods:A single-center, prospective, observational study included 229 gout patients initially diagnosed at the Gout Clinic of Qingdao University from August 2021 to February 2022. The patients underwent MSU assessment of the bilateral feet using DECT. Following enrolment, all patients commenced uric acid-lowering therapy(ULT) and were followed up at 3 and 6 months. Patients who experienced at least one flare within 6 months were compared with those who did not, and the odds ratio( OR) for the risk of gout flares was calculated. Results:Patients who experienced gout flare had a significantly longer disease duration[(6.69±5.42) vs(4.14±4.86) years, P<0.01], a higher number of flares in the past year(4.80±1.73 vs 2.02±1. 23, P<0.01), a higher proportion of fatty livers(11.0% vs 1.4%, P<0.05), and a greater volume of MSU crystals in the feet[(3.52±9.74) vs(0.29±0.98)cm 3,P<0.05] compared to patients without gout flare. The results of the multifactorial logistic regression analysis indicated that the number of flares in the past year( OR=1.295, 95% CI 1.032-1.613, P<0.05) and feet MSU crystal volume( OR=3.245, 95% CI 1.164-9.064, P<0.05) were independent risk factors for gout flares. The receiver operating characteristic(ROC) curve indicated the integration of the MSU prediction model into the clinical prediction model resulted in a comprehensive prediction model with an area under curve(AUC) value of 0.780(95% CI 0.710-0.840), sensitivity of 0.83, and specificity of 0.62. Internal validation of the comprehensive prediction model using the Bootstrap method yielded a C-index of 0.770(95% CI 0.701-0.833) for predicting flares. The calibration curve of the model demonstrated a good fit between the predicted probability of flares and the actual probability, indicating high calibration accuracy. Conclusion:The volume of MSU crystals in the feet is an independent risk factor for flares following ULT. A larger volume of MSU crystals in the foot increases the likelihood of a flare. This study provides a basis for early prediction of flare and a reference for early preventive treatment.
5.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.
6.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.
7.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.
8.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.
9.Surveillance of antifungal resistance in clinical isolates of Candida spp.in East China Invasive Fungal Infection Group from 2018 to 2022
Dongjiang WANG ; Wenjuan WU ; Jian GUO ; Min ZHANG ; Huiping LIN ; Feifei WAN ; Xiaobo MA ; Yueting LI ; Jia LI ; Huiqiong JIA ; Lingbing ZENG ; Xiuhai LU ; Yan JIN ; Jinfeng CAI ; Wei LI ; Zhimin BAI ; Yongqin WU ; Hui DING ; Zhongxian LIAO ; Gen LI ; Hui ZHANG ; Hongwei MENG ; Changzi DENG ; Feng CHEN ; Na JIANG ; Jie QIN ; Guoping DONG ; Jinghua ZHANG ; Wei XI ; Haomin ZHANG ; Rong TANG ; Li LI ; Suzhen WANG ; Fen PAN ; Jing GAO ; Lu JIANG ; Hua FANG ; Zhilan LI ; Yiqun YUAN ; Guoqing WANG ; Yuanxia WANG ; Liping WANG
Chinese Journal of Infection and Chemotherapy 2024;24(4):402-409
Objective To monitor the antifungal resistance of clinical isolates of Candida spp.in the East China region.Methods MALDI-TOF MS or molecular methods were used to re-identify the strains collected from January 2018 to December 2022.Antifungal susceptibility testing was performed using the broth microdilution method.The susceptibility test results were interpreted according to the breakpoints of 2022 Clinical and Laboratory Standards Institute(CLSI)documents M27 M44s-Ed3 and M57s-Ed4.Results A total of 3 026 strains of Candida were collected,65.33%of which were isolated from sterile body sites,mainly from blood(38.86%)and pleural effusion/ascites(10.21%).The predominant species of Candida were Candida albicans(44.51%),followed by Candida parapsilosis complex(19.46%),Candida tropicalis(13.98%),Candida glabrata(10.34%),and other Candida species(0.79%).Candida albicans showed overall high susceptibility rates to the 10 antifungal drugs tested(the lowest rate being 93.62%).Only 2.97%of the strains showed dose-dependent susceptibility(SDD)to fluconazole.Candida parapsilosis complex had a SDD rate of 2.61%and a resistance rate of 9.42%to fluconazole,and susceptibility rates above 90%to other drugs.Candida glabrata had a SDD rate of 92.01%and a resistance rate of 7.99%to fluconazole,resistance rates of 32.27%and 48.24%to posaconazole and voriconazole non-wild-type strains(NWT),respectively,and susceptibility rates above 90%to other drugs.Candida tropicalis had resistance rates of 29.55%and 26.24%to fluconazole and voriconazole,respectively,resistance rates of 76.60%and 21.99%to posaconazole and echinocandins non-wild-type strains(NWT),and a resistance rate of 2.36%to echinocandins.Conclusions The prevalence and species distribution of Candida spp.in the East China region are consistent with previous domestic and international reports.Candida glabrata exhibits certain degree of resistance to fluconazole,while Candida tropicalis demonstrates higher resistance to triazole drugs.Additionally,echinocandins resistance has emerged in Candida albicans,Candida glabrata,Candida tropicalis,and Candida parapsilosis.
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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