1.Expert consensus on apical microsurgery.
Hanguo WANG ; Xin XU ; Zhuan BIAN ; Jingping LIANG ; Zhi CHEN ; Benxiang HOU ; Lihong QIU ; Wenxia CHEN ; Xi WEI ; Kaijin HU ; Qintao WANG ; Zuhua WANG ; Jiyao LI ; Dingming HUANG ; Xiaoyan WANG ; Zhengwei HUANG ; Liuyan MENG ; Chen ZHANG ; Fangfang XIE ; Di YANG ; Jinhua YU ; Jin ZHAO ; Yihuai PAN ; Shuang PAN ; Deqin YANG ; Weidong NIU ; Qi ZHANG ; Shuli DENG ; Jingzhi MA ; Xiuping MENG ; Jian YANG ; Jiayuan WU ; Yi DU ; Junqi LING ; Lin YUE ; Xuedong ZHOU ; Qing YU
International Journal of Oral Science 2025;17(1):2-2
Apical microsurgery is accurate and minimally invasive, produces few complications, and has a success rate of more than 90%. However, due to the lack of awareness and understanding of apical microsurgery by dental general practitioners and even endodontists, many clinical problems remain to be overcome. The consensus has gathered well-known domestic experts to hold a series of special discussions and reached the consensus. This document specifies the indications, contraindications, preoperative preparations, operational procedures, complication prevention measures, and efficacy evaluation of apical microsurgery and is applicable to dentists who perform apical microsurgery after systematic training.
Microsurgery/standards*
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Humans
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Apicoectomy
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Contraindications, Procedure
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Tooth Apex/diagnostic imaging*
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Postoperative Complications/prevention & control*
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Consensus
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Treatment Outcome
2.Analysis and prediction of disease burden of cirrhosis and other chronic liver diseases due to alcohol use in China from 1990 to 2030
Sui ZHU ; Shentong CHEN ; Yingying JIN ; Shangwen LU ; Fengjuan ZOU ; Wenjun MA ; Fangfang ZENG ; Xiaofeng LIANG
Chinese Journal of Epidemiology 2024;45(2):185-191
Objective:To comprehensively understand the disease burden of liver cirrhosis and other chronic liver diseases caused by alcohol use in China from 1990 to 2019, as well as to predict the trends in disease burden from 2020 to 2030.Methods:The analysis utilized data from the Global Burden of Disease study in 2019 (GBD2019). Key indicators such as incidence rate, mortality rate, disability-adjusted life years (DALY), years of life lost due to premature mortality, and years lived with disability were selected to describe the disease burden of alcohol-related liver cirrhosis and other chronic liver diseases in China from 1990 to 2019. The estimated annual percentage change (EAPC) was used to depict the temporal trends in disease burden. Furthermore, a Bayesian age-period-cohort (BAPC) model was constructed using R software to predict the age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) of alcohol-related liver cirrhosis and other chronic liver diseases in China from 2020 to 2030.Results:From 1990 to 2019, the incidence of alcohol-related liver cirrhosis and other chronic liver diseases in China showed an upward trend, with an EAPC of 0.31% (95% CI: 0.10%-0.52%). However, the DALY declined, with an EAPC of -2.81% (95% CI: -2.92% - -2.70%). The ASMR showed a downward trend, with an EAPC of -2.55% (95% CI: -2.66% - -2.45%). The highest incidence of cirrhosis of liver caused by alcohol and other chronic liver diseases was reported in the age group of 35-49 years, while the ASMR increased gradually with age, with a significant rise after the age of 30. The age-standardized DALY rate peaked between the ages of 55 and 64. The disease burden indicators for males were consistently higher than those for females during the same period. According to the predictions of the BAPC model, from 2020 to 2030, the ASIR for cirrhosis of liver caused by alcohol and other chronic liver diseases in the entire population of China was projected to increase from 3.45/100 000 in 2020 to 3.78/100 000 in 2030, a growth of 9.57%. Conversely, the ASMR was expected to decrease from 1.45/100 000 in 2020 to 1.24/100 000 in 2030, a reduction of 14.48%. Conclusions:The disease burden of cirrhosis of liver caused by alcohol and other chronic liver diseases remained serious in China, especially in men and the middle-aged to elderly population. There is a pressing need to prioritize attention and resources towards these groups. Despite the projected decrease in ASMR, the ASIR continued to rise and is expected to persist in its upward trend until 2030.
3.Hepatitis B virus infection,infertility,and assisted reproduction
ZHANG LINGJIAN ; ZHANG FANGFANG ; MA ZHIYUAN ; JIN JIE
Journal of Zhejiang University. Science. B 2024;25(8):672-685
Background:Hepatitis B virus(HBV)is one of the most widespread viruses worldwide and a major cause of hepatitis,cirrhosis,and hepatocellular carcinoma.Previous studies have revealed the impacts of HBV infection on fertility.An increasing number of infertile couples with chronic hepatitis B(CHB)virus infection choose assisted reproductive technology(ART)to meet their fertility needs.Despite the high prevalence of HBV,the effects of HBV infection on assisted reproduction treatment remain limited and contradictory.Objective:The aim of this study was to provide a comprehensive overview of the effect of HBV infection on fertility and discuss its effects on pregnancy outcomes,vertical transmission,pregnancy complications,and viral activity during ART treatment.Methods:We conducted a literature search in PubMed for studies on HBV infection and ART published from 1996 to 2022.Results:HBV infection negatively affected fertility in both males and females.Existing research shows that HBV infection may increase the risk of pregnancy complications in couples undergoing assisted reproduction treatment.The impact of HBV infection on the pregnancy outcomes of ART is still controversial.Current evidence does not support that ART increases the risk of vertical transmission of HBV,while relevant studies are limited.With the development of ART,the risk of HBV reactivation(HBVr)is increasing,especially due to the wide application of immunosuppressive therapy.Conclusions:Regular HBV infection screening and HBVr risk stratification and management are essential to prevent HBVr during ART.The determination of optimal strategy and timing of prophylactic anti-HBV therapy during ART still needs further investigation.
4.Comparative analysis of the changes of thyroid-stimulating hormone and the flow velocity of superior thyroid artery in the treatment of diffuse toxic goiter and Hashimoto's thyroiditis with methimazole
Jianfen WEI ; Naijun WU ; Minghui CHENG ; Xishuang CHENG ; Jie REN ; Yuqian JIN ; Lijing JIAO ; Fangfang KAN ; Jiaxi SHENG
Clinical Medicine of China 2024;40(2):108-113
Objective:To investigate the changes of thyroid hormones and the flow velocity of superior thyroid artery in patients with Graves' disease and Hashimoto's thyrotoxicosis before and after treatment with methimazole.Methods:A case-control study was conducted to select 45 cases of Graves' disease and 45 cases of Hashimoto's thyroiditis from October 2021 to December 2022 in the Department of Endocrinology, North China University of Science and Technology Affiliated Hospital. The changes of thyroid hormone and blood flow velocity of superior thyroid artery in patients with Graves' disease and Hashimoto's thyroiditis before and after treatment with methimazole were analyzed. Measurement data satisfying normal distribution were expressed by xˉ±s, and the mean between two groups was compared by t test. Measurement data not satisfying normal distribution were expressed by M( Q1, Q3), and the median between two groups was compared by Wilcoxon rank sum test. χ 2 test was used to compare the constituent ratio of enumeration data among groups. Results:There was no significant difference in thyroid stimulating hormone (TSH) between the two groups before treatment, and there was no significant difference in TSH between the two groups after 1 month and 3 months of treatment (all P>0.05). The levels of free triiodothyronine (FT3) were (24.09±9.29) pmol/L and (17.41±9.36) pmol/L in Graves' disease group and Hashimoto's thyroiditis group respectively before treatment. FT4 were (60.23±20.82) and (43.47±21.71) pmol/L, respectively, and the peak stolie vloiy (PSV) were (69.53±5.70) and (52.65±4.64) cm/s, respectively in Graves' disease group and Hashimoto's thyroiditis group respectively before treatment. There were significant differences between the two groups ( t values wrere 3.39 and 3.74, Z=13.83, all P<0.001). The difference of FT3 between one month after treatment and before treatment was (-6.36±5.32) and (-12.64±9.08) pmol/L ( t=4.02, P<0.001) and the difference in FT3 between 3 months of treatment and before treatment was (-10.14±9.50) and (-17.80±11.17) pmol/L, respectively ( t=3.51, P<0.001) between the Graves disease group and the Hashimoto's thyroiditis group. The difference in FT4 between the Graves disease group and the Hashimoto's thyroiditis group after 1 month of treatment and before treatment was (-28.47±10.09) and (-20.57±14.48) pmol/L ( t=7.01, P<0.001), and the difference of FT4 was (-47.06±20.57) and (-30.17±20.54) pmol/L ( t=3.91, P<0.001) between the Graves disease group and the Hashimoto toxin group. The difference between one month after treatment and before treatment was (-13.10(-34.10,-2.60)) and (-10.50(-27.5,-0.20)) cm/s ( Z=2.63, P=0.009), respectively. The difference between 3 months and before treatment was (-31.40(-53.20,-12.70)) and (-19.90(-46.00,-4.70)cm/s ( Z=4.40, P<0.001)) between the Graves disease group and the Hashimoto's thyroiditis group, and the difference was statistically significant. Conclusion:Thyroid hormone levels were decreased after treatment with methimazole in patients with diffuse toxic goiter and Hashimoto toxemia, but the difference was not statistically significant. The PSV level of superior thyroid artery in patients with diffuse toxic goiter was significantly lower than that in patients with Hashimoto's thyrotoxicosis.
5.Preliminary testing and analysis of crosstalk in gross α and gross β measurement using an MPC 9604 low background α/β counter
Jiaang XU ; Gang SONG ; Hailiang LI ; Fangfang WU ; Chang JIN ; Nan MIN ; Xiaoshan WANG
Chinese Journal of Radiological Medicine and Protection 2024;44(11):965-970
Objective:To explore the causes of the crosstalk in the gross α and gross β measurement using an MPC 9604 low background α/β counter.Methods:With the A4 copy paper (70 g/m 2), polyethylene (PE) films (8.7 g/m 2), and 304 stainless steel seperately as shielding materials, the gross α and gross β experiments, gamma spectrometry experiments and solid state nuclear track detection (SSNTD) experiments were conducted by using 241Am and 40K standard materials. A comprehensive analysis encompassing statistical analysis and nuclear physics analysis was performed to reveal the impact of contributing factors on the crosstalk in the gross α and gross β measurement with an MPC 9604 low background α/β counter. Results:241Am powder source experimental result: when two sheets of copy paper were used in the experiment, α-rays did not generate one count in the β channel of the low background α/β counter. The same test with the shielding material of two layers of PE films showed that the α count rate further decreased by about 36.5%, while the β count rate hardly changed. The gross α and gross β experiments and γ spectrometry with the shielding material of stainless steel demonstrated that the characteristic γ ray peaking at 59.5 keV of the 241Am powder source did not generate one count in the β channel. 40K powder source experimental result: when the source was covered with steel of total thickness of 0.965 mm in the gross α and gross β experiments, the γ rays of 40K did not generate one count in the β channel. Compared with naked 40K powder source, when source was covered with one and two sheets of copy paper, the gross α count rate decreased approximately from 3.30 × 10 -3 to 1.50 × 10 -3 and 1.75 × 10 -3, respectively. The SSNTD indicated the presence of other α nuclides in 40K powder source. Conclusions:The β counting in the β channel with the 241Am powder source using MPC 9604 low background α/β counter was, instead of α-rays, caused by the internal conversion electrons and the characteristic X rays of 11.870-22.402 keV emitted from the 241Am powder source, thus this is not a true α/β crosstalk. The α counting in α channel with the 40K powder source, except the contribution of impurity α nuclides, was mainly attributed to the α signals arising from β particles when the amplitude of the piled-up β pules exceeded the discrimination threshold of the detector, therefore it is a true crosstalk.
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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