1.Rapid characterization and identification of non-volatile components in Rhododendron tomentosum by UHPLC-Q-TOF-MS method.
Su-Ping XIAO ; Long-Mei LI ; Bin XIE ; Hong LIANG ; Qiong YIN ; Jian-Hui LI ; Jie DU ; Ji-Yong WANG ; Run-Huai ZHAO ; Yan-Qin XU ; Yun-Bo SUN ; Zong-Yuan LU ; Peng-Fei TU
China Journal of Chinese Materia Medica 2025;50(11):3054-3069
This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry*
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Chromatography, High Pressure Liquid/methods*
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Drugs, Chinese Herbal/chemistry*
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Mass Spectrometry/methods*
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Plant Leaves/chemistry*
2.Association of Body Mass Index with All-Cause Mortality and Cause-Specific Mortality in Rural China: 10-Year Follow-up of a Population-Based Multicenter Prospective Study.
Juan Juan HUANG ; Yuan Zhi DI ; Ling Yu SHEN ; Jian Guo LIANG ; Jiang DU ; Xue Fang CAO ; Wei Tao DUAN ; Ai Wei HE ; Jun LIANG ; Li Mei ZHU ; Zi Sen LIU ; Fang LIU ; Shu Min YANG ; Zu Hui XU ; Cheng CHEN ; Bin ZHANG ; Jiao Xia YAN ; Yan Chun LIANG ; Rong LIU ; Tao ZHU ; Hong Zhi LI ; Fei SHEN ; Bo Xuan FENG ; Yi Jun HE ; Zi Han LI ; Ya Qi ZHAO ; Tong Lei GUO ; Li Qiong BAI ; Wei LU ; Qi JIN ; Lei GAO ; He Nan XIN
Biomedical and Environmental Sciences 2025;38(10):1179-1193
OBJECTIVE:
This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study.
METHODS:
A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants.
RESULTS:
Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m 2) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m 2) and obesity (≥ 28.0 kg/m 2) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m 2 ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses.
CONCLUSION
This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans
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Body Mass Index
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China/epidemiology*
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Male
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Female
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Middle Aged
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Prospective Studies
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Rural Population/statistics & numerical data*
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Aged
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Follow-Up Studies
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Adult
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Mortality
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Cause of Death
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Obesity/mortality*
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Overweight/mortality*
3.Visualization and Analysis of Sweat Pore Features in Latent Fingerprints Using Core-Shell Structured Composite Nanofibrous Membrane
Shi-Yue MA ; Ya-Li PEI ; Hong-Yu CHEN ; Xin DU ; Yan-Feng ZHANG ; Rong-Liang MA ; Mei-Qin ZHANG
Chinese Journal of Analytical Chemistry 2025;53(8):1269-1278
Introducing fingerprint level 3 features(especially sweat pores)in fingerprint recognition can significantly improve the value of fingerprints.However,conventional fingerprint visualization methods suffer from issues such as poor stability and reproducibility,insufficient resolution,and feature masking in detecting level 3 features.Electrospun membrane has unique advantages in latent fingerprint(LFP)detection due to its excellent adsorption performance and high specific surface area,and thus its application potential in LFP visualization urgently need to be explored.A novel pore visualization method based on core-shell structured PAN-Flu/PVP composite nanofibrous membrane was proposed in this work.Specifically,the PAN-Flu/PVP composite nanofibrous membrane was prepared via coaxial electrospinning technology,with polyacrylonitrile(PAN)loaded with fluorescein(Flu)as the core and polyvinylpyrrolidone(PVP)as the shell.The experimental results showed that the prepared PAN Flu/PVP composite nanofibrous membrane had a porous structure and excellent adsorption performance.Based on the water solubility of the outer shell PVP and the water induced fluorescence enhancement effect of the core Flu,high-resolution visualization of sweat pores could be achieved within 2 s.The optimization experiment showed that the best quality of sweat latent fingerprints was obtained when the Flu content was 4 mg/mL,the spinning time was 1 h,and the sweating time was 2 min.Through repeated fingerprinting and live fingerprint comparison experiment,the strong stability and high reproducibility of the as-produced membrane in displaying fingerprint sweat pores were finally verified.In summary,the development method could quickly,stably and accurately extract the spatial distribution and activity level of fingerprint sweat pores,which was of great significance for improving the utilization and value of fingerprints.
4.Risk factor analysis and nomogram prediction model construction for pneumonia complicating infectious mononucleosis in adults
Fei HU ; Mei-Juan PENG ; Xu-Yang ZHENG ; Rui LI ; Jia-Yi ZHAN ; Hai-Feng HU ; Hong-Kai XU ; Deng-Hui YU ; Hong DU ; Jian-Qi LIAN
Medical Journal of Chinese People's Liberation Army 2025;50(11):1359-1365
Objective To investigate the risk factors for pneumonia complicating infectious mononucleosis(IM)in adults and construct a nomogram prediction model.Methods A retrospective analysis was conducted on 198 IM patients admitted to the Second Affiliated Hospital of Air Force Medical University from January 2015 to December 2021.Patients were divided into pneumonia group(n=52)and non-pneumonia group(n=146)based on whether pulmonary infection occurred during hospitalization.The baseline data(age,gender,place of onset,etc.),clinical manifestations(maximum body temperature,lymph node enlargement,splenomegaly,etc.),and inflammatory indicators[white blood cell count(WBC),C-reactive protein(CRP),etc.]were compared between the two groups.Kaplan-Meier curves were plotted to analyze the key indicators affecting the hospital stay of IM patients.Multivariate logistic regression was used to analyze the independent risk factors for pneumonia complicating IM in adults and construct a nomogram prediction model based on the identified risk factors.The predictive efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve and the consistency of the model was assessed using the calibration curve.The fit of the model was evaluated using the Hosmer-Lemeshow test.Additionally,the sensitivity,specificity,and accuracy of the model were assessed using confusion matrix.Results Compared with non-pneumonia group,the pneumonia group had a significantly higher proportion of patients from rural areas,with body mass index(BMI)≥24 kg/m2,smoking history,hepatomegaly,fever duration of≥7 d,as well as increased total hospitalization costs and average daily hospitalization costs,and prolonged hospital stay(P<0.05).The proportion of patients with a history of antibiotic use was lower in the pneumonia group(P<0.05).Kaplan-Meier survival analysis showed that patients from rural areas,with BMI≥24 kg/m2,smoking history,no prophylactic use of antibiotics,fever duration≥7 d,and hepatomegaly had significantly prolonged hospital stays(P<0.05).Multivariate logistic regression analysis revealed that living in a rural area(OR=4.089,P<0.05),hepatomegaly(OR=4.082,P<0.05),and elevated WBC(OR=1.205,P<0.05)were independent risk factors for pneumonia complicating IM in adults,while the prophylactic use of antibiotics(OR=0.142,P<0.05)was an independent protective factor.The area under the ROC curve of the constructed nomogram prediction model was 0.827(95%CI 0.762-0.892),and the slope of the calibration curve was close to 1,and the Hosmer-Lemeshow test showed χ2=5.299,P=0.725,indicating good consistency and fit of the prediction model.The results of the confusion matrix assessment showed that the sensitivity of the model was 0.669(0.624-0.773),the specificity was 0.827(0.724-0.930),and the accuracy was 0.732(0.665-0.793).Conclusion The nomogram prediction model based on place of onset,hepatomegaly,the prophylactic use of antibiotics and WBC has excellent fit and discrimination,providing an effective quantitative tool for prognosis assessment of IM.
5.Influencing factors and the Nomogram model to predict early hematoma expansion of intracranial hemorrhage
Fa WU ; Yu-Lin YANG ; Ting-Ting WU ; Rui JIANG ; Jie WU ; Peng WANG ; Fei-Zhou DU ; Hong-Mei YU ; Jian-Hao LI
Medical Journal of Chinese People's Liberation Army 2024;49(5):504-510
Objective To investigate factors influencing the occurrence of early haematoma expansion(HE)in patients with spontaneous intracerebral hemorrhage(sICH),to develop a predictive model and evaluate its predictive efficacy.Methods A retrospective cohort of 238 patients with sICH,admitted to General Hospital of Western Theater Command between January 2017 and December 2022,was analyzed.Patients were categorized into two groups based on the criteria of HE exceeding 33%in relative volume or 6 ml in absolute volume:HE group(n=62)and non-haematoma expansion(NHE)group(n=176).Clinical characteristics,laboratory findings,Non-contrast Computed Tomography(NCCT)imaging,and Glasgow Coma Scale(GCS)scores were compared between the two groups.Multifactorial logistic regression analysis was employed to identify risk factors for HE and to model the probability of its occurrence.The R language rms package was utilized to construct a nomogram model for predicting HE in sICH patients,Additionally,the related clinical,NCCT,and GCS models were constructed.The predictive efficacy of each model for HE in sICH patients was evaluated using area under Receive Operative Characteristic(ROC)curve(AUC),and the clinical application value of each model was assessed using accuracy,sensitivity,specificity,and Jordon's index.The Delong test was applied to analyze differences in the predictive values of the models.Results Significant differences in satellite sign,vortex sign,and history of anticoagulant treatment were observed between two groups(P<0.05).Multifactorial logistic regression analysis revealed independent risk factors for HE in sICH patients,including the first CT examination time,homogeneity,history of anticoagulant medication,volume,maximal diameter,hypodensity sign,island sign,satellite sign,and vortex sign(P<0.05).The AUCs for the constructed clinical model,NCCT model,GCS model and nomogram model in predicting the occurrence of HE in sICH patients were 0.672,0.706,0.518 and 0.754,respectively.The nomogram model demonstrated higher accuracy,sensitivity,Jordon's index and AUC compared with those in the clinical and NCTT models.Conclusions The first CT examination time,homogeneity,history of anticoagulant treatment,volume,maximum diameter,hypodensity sign,island sign,satellite sign,and vortex sign are independent predictors of early HE in sICH patients.The nomogram model,constructed with the above parameters,demonstrated high predictive efficacy for HE and holds potential for clinical application.
6.Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults (version 2024)
Qingde WANG ; Yuan HE ; Bohua CHEN ; Tongwei CHU ; Jinpeng DU ; Jian DONG ; Haoyu FENG ; Shunwu FAN ; Shiqing FENG ; Yanzheng GAO ; Zhong GUAN ; Hua GUO ; Yong HAI ; Lijun HE ; Dianming JIANG ; Jianyuan JIANG ; Bin LIN ; Bin LIU ; Baoge LIU ; Chunde LI ; Fang LI ; Feng LI ; Guohua LYU ; Li LI ; Qi LIAO ; Weishi LI ; Xiaoguang LIU ; Hongjian LIU ; Yong LIU ; Zhongjun LIU ; Shibao LU ; Yong QIU ; Limin RONG ; Yong SHEN ; Huiyong SHEN ; Jun SHU ; Yueming SONG ; Tiansheng SUN ; Yan WANG ; Zhe WANG ; Zheng WANG ; Hong XIA ; Guoyong YIN ; Jinglong YAN ; Wen YUAN ; Zhaoming YE ; Jie ZHAO ; Jianguo ZHANG ; Yue ZHU ; Yingjie ZHOU ; Zhongmin ZHANG ; Wei MEI ; Dingjun HAO ; Baorong HE
Chinese Journal of Trauma 2024;40(2):97-106
Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.
7.Correlations of irradiation dose to urethra with urinary complications in concurrent chemoradiotherapy for locally advanced cervical cancer
Fenghu LI ; Fan MEI ; Yanjun DU ; Xue TIAN ; Lili HU ; Wei HONG ; Hong BAN ; Shuishui YIN ; Yinxiang HU ; Bing LU ; Jiehui LI
Chinese Journal of Radiological Medicine and Protection 2024;44(1):18-23
Objective:To investigate the correlations of urinary adverse reactions with dose to the bladder and urethra during external pelvic irradiation for locally advanced cervical cancer.Methods:This study retrospectively collected relevant dosimetric parameters and urinary symptoms, such as frequent, urgent, and painful urination, from locally advanced cervical cancer patients treated with external pelvic irradiation in the Department of Oncology, Affiliated Hospital of Guizhou Medical University. The dosimetric parameters examined in this study included the maximum, minimum, and mean doses to bladder and urethra (i.e., Dmax, Dmin and Dmean), mean doses received in an area of 0.1, 1, and 2 cm 3 around the planning target volume, D0.1 cm 3, D1 cm 3, D2 cm 3, and percentages of irradiated volumes in the whole organ volume under doses of 5, 10, 15, 20, 25, 30, 35, 40, 45, 50 Gy, V5 Gy, V10 Gy, V15 Gy, V20 Gy, V25 Gy, V30 Gy, V35 Gy, V40 Gy, V45 Gy, V50 Gy. Then the correlations between urinary symptoms and these dosimetric parameters were analyzed using the independent-sample t-test and the Logistic regression model. Results:The median volumes of bladder and urethra were 294.8 and 4.71 cm 3, respectively. Patients were divided into two groups based on the median division. The univariate analysis showed that urethral Dmax, Dmin, Dmean, V5 Gy, V10 Gy, V15Gy, V20 Gy, V25 Gy, V30 Gy, V35 Gy, V40 Gy, V45 Gy and V50 Gy correlated with urinary complications ( t = 14.30, 21.65, 32.19, 33.36, 16.62, 17.91, 21.52, 20.11, 12.27, 37.25, 30.18, 36.24 and 21.98, P<0.05). The multivariate analysis further indicates that urethral D2 cm 3, V20 Gy, V40 Gy and Bladder V40 Gy, D1 cm 3, D2 cm 3 were independent predictors of grade 2 urinary adverse reactions ( P<0.05). Conclusions:This study reported the correlations of relevant dosimetric parameters of urethra with urinary toxicity during external pelvic irradiation. It holds that urethral D2 cm 3, V20 Gy and V40 Gy should be restricted to minimize the risks of grade 2 urinary complications.
8.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.
9.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.
10.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.

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