1.Exploration and validation of optimal cut-off values for tPSA and fPSA/tPSA screening of prostate cancer at different ages
Xiaomin LIU ; Hongyuan DUAN ; Dongqi ZHANG ; Chong CHEN ; Yuting JI ; Yunmeng ZHANG ; Zhuowei FENG ; Ya LIU ; Jingjing LI ; Yu ZHANG ; Chenyang LI ; Yacong ZHANG ; Lei YANG ; Zhangyan LYU ; Fangfang SONG ; Fengju SONG ; Yubei HUANG
Chinese Journal of Oncology 2024;46(4):354-364
Objective:To determine the total and age-specific cut-off values of total prostate specific antigen (tPSA) and the ratio of free PSA divided total PSA (fPSA/tPSA) for screening prostate cancer in China.Methods:Based on the Chinese Colorectal, Breast, Lung, Liver, and Stomach cancer Screening Trial (C-BLAST) and the Tianjin Common Cancer Case Cohort (TJ4C), males who were not diagnosed with any cancers at baseline since 2017 and received both tPSA and fPSA testes were selected. Based on Cox regression, the overall and age-specific (<60, 60-<70, and ≥70 years) accuracy and optimal cut-off values of tPSA and fPSA/tPSA ratio for screening prostate cancer were evaluated with time-dependent receiver operating characteristic curve (tdROC) and area under curve (AUC). Bootstrap resampling was used to internally validate the stability of the optimal cut-off value, and the PLCO study was used to externally validate the accuracy under different cut-off values.Results:A total of 5 180 participants were included in the study, and after a median follow-up of 1.48 years, a total of 332 prostate cancer patients were included. In the total population, the tdAUC of tPSA and fPSA/tPSA screening for prostate cancer were 0.852 and 0.748, respectively, with the optimal cut-off values of 5.08 ng/ml and 0.173, respectively. After age stratification, the age specific cut-off values of tPSA in the <60, 60-<70, and ≥70 age groups were 3.13, 4.82, and 11.54 ng/ml, respectively, while the age-specific cut-off values of fPSA/tPSA were 0.153, 0.135, and 0.130, respectively. Under the age-specific cut-off values, the sensitivities of tPSA screening for prostate cancer in males <60, 60-70, and ≥70 years old were 92.3%, 82.0%, and 77.6%, respectively, while the specificities were 84.7%, 81.3%, and 75.4%, respectively. The age-specific sensitivities of fPSA/tPSA for screening prostate cancer were 74.4%, 53.3%, and 55.9%, respectively, while the specificities were 83.8%, 83.7%, and 83.7%, respectively. Both bootstrap's internal validation and PLCO external validation provided similar results. The combination of tPSA and fPSA/tPSA could further improve the accuracy of screening.Conclusion:To improve the screening effects, it is recommended that age-specific cut-off values of tPSA and fPSA/tPSA should be used to screen for prostate cancer in the general risk population.
2.Exploration and validation of optimal cut-off values for tPSA and fPSA/tPSA screening of prostate cancer at different ages
Xiaomin LIU ; Hongyuan DUAN ; Dongqi ZHANG ; Chong CHEN ; Yuting JI ; Yunmeng ZHANG ; Zhuowei FENG ; Ya LIU ; Jingjing LI ; Yu ZHANG ; Chenyang LI ; Yacong ZHANG ; Lei YANG ; Zhangyan LYU ; Fangfang SONG ; Fengju SONG ; Yubei HUANG
Chinese Journal of Oncology 2024;46(4):354-364
Objective:To determine the total and age-specific cut-off values of total prostate specific antigen (tPSA) and the ratio of free PSA divided total PSA (fPSA/tPSA) for screening prostate cancer in China.Methods:Based on the Chinese Colorectal, Breast, Lung, Liver, and Stomach cancer Screening Trial (C-BLAST) and the Tianjin Common Cancer Case Cohort (TJ4C), males who were not diagnosed with any cancers at baseline since 2017 and received both tPSA and fPSA testes were selected. Based on Cox regression, the overall and age-specific (<60, 60-<70, and ≥70 years) accuracy and optimal cut-off values of tPSA and fPSA/tPSA ratio for screening prostate cancer were evaluated with time-dependent receiver operating characteristic curve (tdROC) and area under curve (AUC). Bootstrap resampling was used to internally validate the stability of the optimal cut-off value, and the PLCO study was used to externally validate the accuracy under different cut-off values.Results:A total of 5 180 participants were included in the study, and after a median follow-up of 1.48 years, a total of 332 prostate cancer patients were included. In the total population, the tdAUC of tPSA and fPSA/tPSA screening for prostate cancer were 0.852 and 0.748, respectively, with the optimal cut-off values of 5.08 ng/ml and 0.173, respectively. After age stratification, the age specific cut-off values of tPSA in the <60, 60-<70, and ≥70 age groups were 3.13, 4.82, and 11.54 ng/ml, respectively, while the age-specific cut-off values of fPSA/tPSA were 0.153, 0.135, and 0.130, respectively. Under the age-specific cut-off values, the sensitivities of tPSA screening for prostate cancer in males <60, 60-70, and ≥70 years old were 92.3%, 82.0%, and 77.6%, respectively, while the specificities were 84.7%, 81.3%, and 75.4%, respectively. The age-specific sensitivities of fPSA/tPSA for screening prostate cancer were 74.4%, 53.3%, and 55.9%, respectively, while the specificities were 83.8%, 83.7%, and 83.7%, respectively. Both bootstrap's internal validation and PLCO external validation provided similar results. The combination of tPSA and fPSA/tPSA could further improve the accuracy of screening.Conclusion:To improve the screening effects, it is recommended that age-specific cut-off values of tPSA and fPSA/tPSA should be used to screen for prostate cancer in the general risk population.
3.Summary of the best evidence for the management of pregnant women during pregnancy after cervical cerclage
Meihui ZHAO ; Huiren ZHUANG ; Qiuxia CHEN ; Fangming FENG ; Wenjing WANG ; Fangfang YANG
Chinese Journal of Practical Nursing 2024;40(17):1310-1318
Objective:To retrieve, screen, evaluate and synthesize evidence related to the management of pregnant women during pregnancy after cervical cerclage to provide a basis for clinical practice.Methods:According to the "6S" evidence resource pyramid model, the system searched of all evidence on the management of pregnant women after cervical cerclage in databases suchas UpTo Date, BMJ Best Clinical Practice, International Guidelines Network, American Guidelines Network, World Health Organization website, Yimaitong, Metz Medical website, Clinical Guidelines website, American College of Obstetricians and Gynaecologists, Royal College of Obstetricians and Gynaecologists of the United Kingdom, Canadian College of Obstetricians and Gynaecologists, French College of Obstetricians and Gynaecologists, European Association of Perinatal Medicine, Cochrane Library, the Joanna Briggs Institute (JBI), the Centre for Evidence-Based Health Care Database, PubMed, Embase, Scopus, Web of Science, CNKI, Wanfang Database, VIP Database, and China Biomedical Literature Database, including best dicision practices, guidelines, expert consensus, evidence summary, systematic reviews, Meta-analysis. The search time limit was the establishment of the database to March 1, 2023, and the evidence was extracted and summarized according to the theme after the two researchers independently evaluate the quality of the literature.Results:A total of 8 studies were selected, including 2 expert consensuses, 2 systematic reviews and 4 guidelines. Through literature reading, evidence extraction and classification, 23 pieces of best evidence were summarized from seven aspects: systematic management, activity management, medication management, health behavior management, pregnancy supervision, supervision of the timing of cerclage removal and supervision of psychological state.Conclusions:The best evidence quality and autuority of pregnancy management for pregnamt women after cervical cerclage surgery summarized in the study are high. It was recommended to strengthen the management of pregnant women during pregnancy after cervical cerclage, dynamically and continuously assess the pregnancy status of pregnant women, and prudently selected evidence to improve the prenatal examination process, ensure the safety of mothers and babies, and reduce the occurrence of complications. Overall, effective management of pregnant women during pregnancy after cervical cerclage required a combination of many factors to ensure the health and safety of the mother and baby.
4.The significance of detecting human cytomegalovirus UL95 antigenic epitope peptide in the diagnosis of SLE
Ya HU ; Chenyu XU ; Wei QIANG ; Huidi ZHANG ; Fangfang FENG
Chinese Journal of Laboratory Medicine 2024;47(9):1042-1051
Objective:To explore the clinical significance of the dominant B-cell epitope peptide of the human cytomegalovirus (HCMV) UL95 gene, as well as the correlation between the plasma UL95 specific antibody levels and clinical indicators in systemic lupus erythematosus (SLE) patients, in order to find auxiliary diagnostic indicators for SLE.Methods:A non-randomized control study was conducted to analyze the sequencial characteristics and polymorphisms of HCMV UL95 gene, and bioinformatics analysis and chemical synthesis were used to synthesize UL95 dominant B cell epitope short peptides, which were used as coating antigens. Enzyme-linked immunosorbent assay (ELISA) assay was used to detect the specific antibody levels of plasma UL95 of 97 SLE patients and 35 healthy controls (HC). Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic value of UL95 short peptide antibodies for SLE diagnosis. Pearson correlation test was used to analyze the correlation between UL95 specific antibody levels and clinical indicators in SLE patients.Results:The nucleotide sequence similarity of UL95 gene was 92.9%-100%, and the amino acid sequence similarity was 92.1%-100%, whose sequences were highly conserved and homologous. A comprehensive prediction of multiple parameters resulted in 6 possible dominant B cell epitopes, named (Bp1, Bp2, Bp3, Bp4, Bp5, Bp6) respectively. The ELISA results showed that the levels of plasma UL95 specific antibodies (0.35±0.12) in SLE patients were significantly higher than those of the HC group (0.28±0.10)( t=3.091, P=0.002). The area under the ROC curve for distinguishing SLE and HC was 0.703, with a sensitivity of 54.6% and a specificity of 88.6%. In addition, the UL95 specifific antibody levels ( OD value) in the middle-high activity subgroup (systemic lupus erythematosus disease activity index, SLEDAI≥4) were higher (0.36±0.10) than those in the low activity subgroup (SLEDAI<4)(0.30±0.07) ( t=?2.055, P=0.044). UL95 specific antibody levels were positively correlated with clinical indicators such as total immunoglobulin G (IgG) and total immunoglobulin M (IgM), while negatively correlated with complement component 3 (C3), complement component 4 (C4), and platelet count. Conclusions:The antibody level of UL95 is closely related to the activity of lupus disease. The Bp1 (10-21) peptide segment of UL95 has important significance for the auxiliary diagnosis of SLE and is expected to become a new reference indicator.
5.Evaluation of the value of patient data-based real-time quality control in improving the effectiveness of indoor quality management
Minge LIU ; Fangfang FENG ; Xucai DONG ; Hailing XIONG ; Bin LI ; Dongmei WEN ; Xiaoke HAO ; Xianfei ZENG
Chinese Journal of Laboratory Medicine 2024;47(10):1186-1191
Objective:To explore the application value of patient data-based real-time quality control (PBRTQC) in enhancing the effectiveness of internal quality control (IQC) management.Methods:From the PBRTQC real-time quality control intelligent monitoring platform integrated with the laboratory information system (LIS), a total of 35,631 test results of red blood cell (RBC) count, white blood cell (WBC) count, and dehydroepiandrosterone sulfate (DHEA-S) were collected from patients of the Department of General Xi'an Area Medical Laboratory Center from August 1, 2023, to April 1, 2024. The platform was used in patient data distribution characteristics test, EWMA real-time quality control chart procedure establishment, performance validation, effect evaluation, best procedure selection, and real-time operation. The performance evaluation indexes of the best PBRTQC procedure establishment, the cut-off limit range, weighting coefficient, cumulative mean, standard deviation (SD), coefficient of variation ( CV) of the EWMA real-time quality control chart, and the cumulative mean, SD, and CV of its internal quality control data in the same period were counted, and at the same time compared with the quality target (1/3TEa). Coefficient of variation analyses were performed to compare the quality control status of PBRTQC and conventional internal quality control in the presence of warning or alarm prompts based on quality control process records, and alarm messages. Results:The evaluation indexes of the optimal procedures for RBC count, WBC count, and DHEA-S were the probability of error detection (Ped) between 93%-97% and greater than 90%, the false positive rate (FPR) between 0.0%-0.5%, the false negative rate (FNR) between 3.0%-7.0%, and the average number of the patient sample until error detection (ANPed) between 5-11, which is in line with the optimal quality control efficacy quality requirements for the PBRTQC procedure. The patient outcome cut-off concentrations for the optimal procedure EWMA quality control charts ranged from RBC count (3.92-5.16)×10 12/L, WBC count (4.28-7.50)×10 9/L, and DHEA-S (830-2 160) μg/L; (2 160-4 210) μg/L. The weighting coefficients were 0.05, 0.03, and 0.03, respectively. The real-world application of the EWMA real-time quality control charts showed stable and excellent analytical performance of the measurement system, such as out-of-control alarm: RBC count, 1 true alarm, Ped of 95.85%, and FPR of 0%. The cumulative CV of EWMA was less than the quality target; the cumulative CV of DHEA-S was 7.66% and 9.47%, respectively, and the cumulative CV of low level was greater than the quality target (8.33%), and the cumulative CV of high and low levels were 4.12% and 6.25%. Conclusion:The PBRTQC EWMA method can monitor the patient data - in real-time and continuous way. It can also dynamically identify and provide early indication of small changes in analytical performance during the analysis process, and can be used as a supplement to quality control products to improve the efficacy of laboratory quality management.
6.Nursing care of a patient before operation with mechanical circulation-assisted bridging heart transplantation
Xuqin LI ; Jiehui FENG ; Fangfang HUANG ; Chao YU ; Shiyu LIANG ; Xiao WANG ; Xufang LI ; Han ZHU
Chinese Journal of Nursing 2024;59(9):1114-1118
To summarize the nursing care of a patient with acute myocardial infarction complicated with cardiogenic shock before operation.The main nursing points are as follows:in the acute stage,the integrated rescue was implemented with rapid on-machine coordination of external cardiopulmonary resuscitation,multidisciplinary collaboration to ensure safe patient transport;during the bridging period,the combined operation care of extracorporeal membrane oxygenation,intra-aortic balloon counter pulsation and continuous kidney replacement therapy was carried out with goal-oriented anticoagulation care,prevention of catheter-related infection with the assistance of mechanical circulation,and neurological function monitoring.The patient successfully passed the waiting period for heart transplantation and underwent heart transplantation 21 days after admission.With the follow-up for 1 year,the patient recovered well.
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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