1.Design of automatic urine volume detection and collection device
Yan CHEN ; De-Zhao ZHAI ; Xiao-Quan ZHANG ; Fu-Long LIU ; Xiao-Tao ZHANG ; Yong-Mei ZHANG ; Wei CEHN ; Fang ZHANG ; Guo-Hui WU ; Jun DENG ; Dan LI
Chinese Medical Equipment Journal 2024;45(4):66-69
Objective To develop an automatic urine volume detection and collection device to solve the problems of routine urine test.Methods An automatic urine volume detection and collection device was developed with the components of a main control system,a detection system,a prompting system and a grasping and moving system.The main control system consisted of two STM32 microcontrollers and a reset switch;the detection system was made up of a weighing module,an infrared module and indicator lights,which had its urine volume automatic detection algorithm developed based on the Keil5 platform;the prompting system realized voice broadcasting through the voice module fixed on the back panel of the box;the grasping and moving system was composed of a rail drive motor(86CM stepper motor),a photoelectric switch and a motorized gripper.Results The device developed tested urine samples with an accuracy of 99.44%,and could collect qualified samples automatically and quickly.Conclusion The device developed detects urine volume and collects samples automatically,and enhances the accuracy and efficiency of urine examination.[Chinese Medical Equipment Journal,2024,45(4):66-69]
2.Relationship between lipid metabolism molecules in plasma and carotid atheroscle-rotic plaques,traditional cardiovascular risk factors,and dietary factors
Jing HE ; Zhongze FANG ; Ying YANG ; Jing LIU ; Wenyao MA ; Yong HUO ; Wei GAO ; Yangfeng WU ; Gaoqiang XIE
Journal of Peking University(Health Sciences) 2024;56(4):722-728
Objective:To explore the relationship between lipid metabolism molecules in plasma and carotid atherosclerotic plaques,traditional cardiovascular risk factors and possible dietary related factors.Methods:Firstly,among 1 312 community people from those who participated in a 10-year follow-up study of subclinical atherosclerosis cohort in Shijingshan District,Beijing,85 individuals with 2 or more carotid soft plaques or mixed plaques and 89 healthy individuals without plaques were selected according to the inclusive and the exclusive criteria(<70 years,not having clinical cardiovascular disease and other diseases,etc.).Secondly,10 cases and 10 controls were randomly selected in the above 85 and 89 individuals respectively.Carotid plaques were detected using GE Vivid i Ultrasound Machine with 8L de-tector.Lipid metabolism molecules were detected by high performance liquid chromatography-mass spec-trometry.The detection indexes included 113 lipid metabolism molecules.Traditional cardiovascular risk factors were collected by unified standard questionnaires,and dietary related factors were collected by main dietary frequency and weight scale.The difference of lipid metabolism molecules between the case group and the control group was analyzed by Wilcoxin rank test.In the control group,the Spearman cor-relation method was used to analyze the correlation between statistically significant lipid metabolism molecules and traditional cardiovascular risk factors and dietary factors.Results:Among the 113 lipid metabolism molecules,53 lipid metabolism molecules were detected.C24∶0 sphingomyelin(SM),C22∶0/C24∶0 ceramide molecules,C18∶0 phosphoethanolamine(PE)molecules,and C18∶0/C18∶2(Cis)phosphatidylcholine(PC)were significantly higher in the carotid atherosclerotic plaque group than in the control group.The correlation analysis showed that C24∶0 SM was significantly positively correlated with low density lipoprotein cholesterol(LDL-C,r=0.636,P<0.05),C18∶2(Cis)PC(DLPC)was sig-nificantly positively correlated with systolic pressure(r=0.733,P<0.05),C18∶0 PE was significantly positively correlated with high sensitivity C-response protein(r=0.782,P<0.01),C22∶0,C24∶0 ce-ramide and C18∶0 PE were negatively correlated with vegetable intake(r=-0.679,P<0.05;r=-0.711,P<0.05;r=-0.808,P<0.01),C24∶0 ceramide was also negatively correlated with beans food intake(r=-0.736,P<0.05)in the control group.Conclusion:The increase of plasma C24∶0 SM,C22∶0,C24∶0 ceramide,C18∶0PE,C18∶2(Cis)PC(DLPC),C18∶0PC(DSPC)may be new risk factors for human atherosclerotic plaques.These molecules may be related to blood lipid,blood pres-sure or inflammatory level and the intake of vegetables and soy products,but the nature of the association needs to be verified in a larger sample population.
3.Analysis of the causes of cage subsidence after oblique lateral lumbar interbody fusion
Zhong-You ZENG ; Ping-Quan CHEN ; Xing ZHAO ; Hong-Fei WU ; Jian-Qiao ZHANG ; Xiang-Qian FANG ; Yong-Xing SONG ; Wei YU ; Fei PEI ; Shun-Wu FAN ; Guo-Hao SONG ; Shi-Yang FAN
China Journal of Orthopaedics and Traumatology 2024;37(1):33-44
Objective To observe the cage subsidence after oblique lateral interbody fusion(OLIF)for lumbar spondylo-sis,summarize the characteristics of the cage subsidence,analyze causes,and propose preventive measures.Methods The data of 144 patients of lumbar spine lesions admitted to our hospital from October 2015 to December 2018 were retrospectively ana-lyzed.There were 43 males and 101 females,and the age ranged from 20 to 81 years old,with an average of(60.90±10.06)years old.Disease types:17 patients of lumbar intervertebral disc degenerative disease,12 patients of giant lumbar disc hernia-tion,5 patients of discogenic low back pain,33 patients of lumbar spinal stenosis,26 patients of lumbar degenerative spondy-lolisthesis,28 patients of lumbar spondylolisthesis with spondylolisthesis,11 patients of adjacent vertebral disease after lumbar internal fixation,7 patients of primary spondylitis in the inflammatory outcome stage,and 5 patients of lumbar degenerative scoliosis.Preoperative dual-energy X-ray bone mineral density examination showed 57 patients of osteopenia or osteoporosis,and 87 patients of normal bone density.The number of fusion segments:124 patients of single-segment,11 patients of two-seg-ment,8 patients of three-segment,four-segment 1 patient.There were 40 patients treated by stand-alone OLIF,and 104 patients by OLIF combined with posterior pedicle screw.Observed the occurrence of fusion cage settlement after operation,conducted monofactor analysis on possible risk factors,and observed the influence of fusion cage settlement on clinical results.Results All operations were successfully completed,the median operation time was 99 min,and the median intraoperative blood loss was 106 ml.Intraoperative endplate injury occurred in 30 patients and vertebral fracture occurred in 5 patients.The mean follow-up was(14.57±7.14)months from 6 to 30 months.During the follow-up,except for the patients of primary lumbar interstitial in-flammation and some patients of lumbar spondylolisthesis with spondylolisthesis,the others all had different degrees of cage subsidence.Cage subsidence classification:119 patients were normal subsidence,and 25 patients were abnormal subsidence(23 patients were grade Ⅰ,and 2 patients were grade Ⅱ).There was no loosening or rupture of the pedicle screw system.The height of the intervertebral space recovered from the preoperative average(9.48±1.84)mm to the postoperative average(12.65±2.03)mm,and the average(10.51±1.81)mm at the last follow-up.There were statistical differences between postop-erative and preoperative,and between the last follow-up and postoperative.The interbody fusion rate was 94.4%.The low back pain VAS decreased from the preoperative average(6.55±2.2 9)to the last follow-up(1.40±0.82),and there was statistically significant different.The leg pain VAS decreased from the preoperative average(4.72±1.49)to the final follow-up(0.60± 0.03),and the difference was statistically significant(t=9.13,P<0.000 1).The ODI index recovered from the preoperative av-erage(38.50±6.98)%to the latest follow-up(11.30±3.27)%,and there was statistically significant different.The complication rate was 31.3%(45/144),and the reoperation rate was 9.72%(14/144).Among them,8 patients were reoperated due to fusion cage subsidence or displacement,accounting for 57.14%(8/14)of reoperation.The fusion cage subsidence in this group had obvious characteristics.The monofactor analysis showed that the number of abnormal subsidence patients in the osteopenia or osteoporosis group,Stand-alone OLIF group,2 or more segments fusion group,and endplate injury group was higher than that in the normal bone mass group,OLIF combined with pedicle screw fixation group,single segment fusion group,and no endplate injury group,and the comparison had statistical differences.Conclusion Cage subsidence is a common phenomenon after 0-LIF surgery.Preoperative osteopenia or osteoporosis,Stand-alone OLIF,2 or more segments of fusion and intraoperative end-plate injury may be important factors for postoperative fusion cage subsidence.Although there is no significant correlation be-tween the degree of cage subsidence and clinical symptoms,there is a risk of cage migration,and prevention needs to be strengthened to reduce serious complications caused by fusion of cage subsidence,including reoperation.
4.Clinical efficacy of patient-specific instrumentation assisted unicompartmental knee arthroplasty
Xiangyu MENG ; Zhixue WANG ; Peng WU ; Huanming FANG ; Peng ZHAO ; Xu WANG ; Yong DING
Chinese Journal of Orthopaedics 2024;44(22):1441-1449
Objective:To investigate the postoperative prosthesis position and early clinical efficacy of 3D printing patient-specific instrumentation (PSI)-assisted unicompartmental knee arthroplasty (UKA).Methods:The clinical data of 15 patients (17 knees, PSI group) with medial compartment knee osteoarthritis who underwent PSI-assisted UKA in the Second Affiliated Hospital, the Air Force Medical University from May to August 2023 were retrospectively analyzed, matched with fifteen patients (17 knees, non-PSI group) with medial compartment knee osteoarthritis undergoing conventional UKA. The differences in the prosthesis placement positions in the postoperative X-ray films between the two groups were compared, including the coronal varus-valgus angles of the tibial and femoral prostheses, the sagittal posterior inclination angle of the tibial prosthesis, the flexion-extension angle of the femoral prosthesis, and the height of the reconstructed joint line. The indicators related to the lower limb alignment (including the femoral valgus angle, the lateral femoral angle, the hip-knee-ankle angle, and the femur-tibia angle) and the range of motion of the knee joint before and after the operation were compared. The Oxford knee score (OKS), American Knee Society (AKS) knee score and function score, and the visual analogue scale (VAS) were used to evaluate the clinical effects of the two groups.Results:In the PSI group, the coronal varus-valgus angle of the tibial prosthesis was 1.6°±0.3° after the operation, and the sagittal posterior inclination angle was 5.7°±0.8°. The coronal varus-valgus angle of the femoral prosthesis was -0.5°±1.5°, and the sagittal flexion-extension angle was 4.0°±1.9°. In the non-PSI group, the corresponding angles were 2.3°±0.6°, 4.5°±1.0°, 1.4°±1.5°, and 7.3°±2.2° respectively with significant differences between the two groups ( P<0.05). The OKS of the PSI group before and after the operation were 26.5±1.8 and 38.6±4.1 points respectively. The AKS knee score were 56.9±8.6 and 89.2±7.2 points. The AKS function score were 70.1±4.2 and 77.5±9.4 points. The VAS were 4.5±3.7 and 2.3±0.3 points, and the range of motion of the knee joint were 115.2°±4.8° and 125.9°±4.6° with significant differences ( P<0.05). The OKS of the non-PSI group before and after the operation were 25.3±6.2 and 38.2±3.5 points respectively. The AKS knee score were 50.6±9.3 and 84.5±6.6 points. The AKS function score were 73.4±3.9 and 77.2±4.8 points. The VAS were 5.8±2.4 and 2.5±1.6 points, and the range of motion of the knee joint were 113.6°±6.7° and 122.3°±5.0° with significant differences ( P<0.05). There were inter-group differences in the AKS knee score and the range of motion of the knee joint after the operation between the two groups with significant differences ( P<0.05). Conclusion:PSI guides-assisted UKA can effectively correct the lower limb alignment of patients and improve knee joint function with good short-term efficacy. Compared with conventional UKA, PSI guides-assisted UKA is less time-consuming with higher precision in prosthesis installation position and fewer post-operative complications.
5.Clinical features and prognosis of children with fungal bloodstream infection following chemotherapy for acute leukemia
Kai-Zhi WENG ; Chun-Ping WU ; Shu-Quan ZHUANG ; Shu-Xian HUANG ; Xiao-Fang WANG ; Yong-Zhi ZHENG
Chinese Journal of Contemporary Pediatrics 2024;26(10):1086-1092
Objective To investigate the clinical features and prognosis of children with fungal bloodstream infection(BSI)following chemotherapy for acute leukemia(AL).Methods A retrospective analysis was performed on 23 children with fungal BSI following chemotherapy for AL in three hospitals in Fujian Province,China,from January 2015 to December 2023.Their clinical features and prognosis were analyzed.Results Among all children following chemotherapy for AL,the incidence rate of fungal BSI was 1.38%(23/1 668).At the time of fungal BSI,87%(20/23)of the children had neutrophil deficiency for more than one week,and all the children presented with fever,while 22%(5/23)of them experienced septic shock.All 23 children exhibited significant increases in C-reactive protein and procalcitonin levels.A total of 23 fungal isolates were detected in peripheral blood cultures,with Candida tropicalis being the most common isolate(52%,12/23).Caspofungin or micafungin combined with liposomal amphotericin B had a relatively high response rate(75%,12/16),and the median duration of antifungal therapy was 3.0 months.The overall mortality rate in the patients with fungal BSI was 35%(8/23),and the attributable death rate was 22%(5/23).Conclusions Fungal BSI following chemotherapy in children with AL often occurs in children with persistent neutrophil deficiency and lacks specific clinical manifestations.The children with fungal BSI following chemotherapy for AL experience a prolonged course of antifungal therapy and have a high mortality rate,with Candida tropicalis being the most common pathogen.
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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