2.Expert consensus on imaging diagnosis and analysis of early correction of childhood malocclusion.
Zitong LIN ; Chenchen ZHOU ; Ziyang HU ; Zuyan ZHANG ; Yong CHENG ; Bing FANG ; Hong HE ; Hu WANG ; Gang LI ; Jun GUO ; Weihua GUO ; Xiaobing LI ; Guangning ZHENG ; Zhimin LI ; Donglin ZENG ; Yan LIU ; Yuehua LIU ; Min HU ; Lunguo XIA ; Jihong ZHAO ; Yaling SONG ; Huang LI ; Jun JI ; Jinlin SONG ; Lili CHEN ; Tiemei WANG
International Journal of Oral Science 2025;17(1):21-21
Early correction of childhood malocclusion is timely managing morphological, structural, and functional abnormalities at different dentomaxillofacial developmental stages. The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion. This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence, aiming to provide general guidance on appropriate imaging examination selection, comprehensive and accurate imaging assessment for early orthodontic treatment patients.
Humans
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Malocclusion/diagnostic imaging*
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Child
;
Consensus
3.Construction and validation of prediction models for delayed encephalopathy after acute carbon monoxide poisoning based on machine learning
Yanwu YU ; Yan ZHANG ; Ding YUAN ; Huihui HAO ; Fang YANG ; Hongyi YAN ; Pin JIANG ; Mengnan GUO ; Zhigao XU ; Changhua SUN ; Gaiqin YAN ; Lu CHE ; Jianjun GUO ; Jihong CHEN ; Yan LI ; Yanxia GAO
Chinese Journal of Emergency Medicine 2025;34(10):1403-1409
Objective:s To investigate the risk factors for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) in patients with acute carbon monoxide poisoning (ACOP) and to develop predictive models based on machine learning algorithms.Methods:Patients with ACOP hospitalized at the First Affiliated Hospital of Zhengzhou University from August 2019 to October 2024 were included, with the occurrence of DEACMP as the outcome measure. The dataset was randomly divided into training and validation sets at a ratio of 7:3. Lasso regression was used to select features influencing the outcome in training sets. Nine machine learning models—including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—were constructed. Receiver operating characteristic (ROC) curves were plotted and the area under the curve (AUC) calculated for each model. Calibration curves were used to assess accuracy, and decision curve analysis (DCA) was applied to evaluate clinical utility. The SHapley Additive exPlanations (SHAP) method was employed to visualize and interpret the best-performing model.Results:A total of 264 ACOP patients were included, of whom 54 (20.5%) developed DEACMP. Lasso regression identified eight key feature variables. Based on these factors, predictive models were constructed, showing good AUC stability across the nine machine learning models in both training (0.92–0.99) and validation sets (0.85–0.91). The RF model performed best, with an AUC of 0.99 in the training set and 0.90 in the validation set; its calibration curve and DCA curve also demonstrated excellent performance. SHAP analysis of the RF model revealed the importance ranking of factors from highest to lowest as follows: Glasgow Coma Scale (GCS) score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, diastolic blood pressure (DBP), and drinking history.Conclusions:The RF model exhibited the highest predictive performance for DEACMP occurrence in ACOP patients. The influencing factors, ranked in order of importance from highest to lowest, are as follows: GCS score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, DBP, and drinking history.
4.Establishment and verification of a predictive model for feeding intolerance in premature infants
Chinese Journal of Practical Nursing 2024;40(11):816-822
Objective:The prediction model of feeding intolerance in preterm infants was established and validated to provide guidance for clinical practice.Methods:This was a case-control study. A retrospective analysis was conducted on 210 premature infants with gestational age less than 34 weeks from September 2022 to May 2023. They were divided into training and validation sets in a 1∶1 ratio. The univariate and multivariate binary Logistic regression analysis were performed on training set samples, first identified the risk factors for feeding intolerance occurrence, and established a premature feeding intolerance risk prediction model based on these risk factors. Visualized the model using a column chart. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and clinical decision curves in the training and validation sets, respectively. The ROC curve was used to evaluate the differentiation ability of the model, the calibration curve was used to evaluate the consistency of the model, and clinical decision-making was used to evaluate the net benefit status of patients when the model guides clinical interventions.Results:Among them, there were 84 cases in the feeding tolerance and 126 cases in the feeding intolerance. There were 53 males and 31 females with feeding tolerance aged (32.38 ± 1.37) weeks and 73 males and 53 females with feeding intolerance aged (30.01 ± 2.14) weeks. Through univariate Logistic regression analysis of 12 related variables, there were significant differences between the feeding tolerance premature infants and the feeding intolerance premature infants in 8 variables of premature birth weight, birth asphyxia, caffeine use, delayed defecation, gestational age, lactation time, non-invasive ventilation time, and invasive ventilation time ( OR values were 0.032-18.706, all P<0.05). Multiple Logistic regression ultimately screened out three variables, namely premature infant body mass, delayed defecation, and non-invasive ventilation time ( OR = 0.073, 4.926, 1.244, all P<0.05). The area under the ROC curve of the training and validation sets were 0.906 and 0.876, respectively. The calibration curves of the training and validation sets indicated that the model had high consistency. The Hosmer-Lemeshow goodness of fit test showed that χ2 = 7.92, P = 0.442. Conclusions:The prediction model established in this study has high discrimination, calibration, and clinical practical value, and can accurately predict the risk of feeding intolerance in premature infants, providing reference basis for timely nursing and clinical intervention.
5.QL1604 plus paclitaxel-cisplatin/ carboplatin in patients with recurrent or metastatic cervical cancer:an open-label, single-arm, phase II trial
Cheng FANG ; Yun ZHOU ; Yanling FENG ; Liping HE ; Jinjin YU ; Yuzhi LI ; Mei FENG ; Mei PAN ; Lina ZHAO ; Dihong TANG ; Xiumin LI ; Buzhen TAN ; Ruifang AN ; Xiaohui ZHENG ; Meimei SI ; Baihui ZHANG ; Lingyan LI ; Xiaoyan KANG ; Qi ZHOU ; Jihong LIU
Journal of Gynecologic Oncology 2024;35(6):e77-
Objective:
QL1604 is a highly selective, humanized monoclonal antibody against programmed death protein 1. We assessed the efficacy and safety of QL1604 plus chemotherapy as first-line treatment in patients with advanced cervical cancer.
Methods:
This was a multicenter, open-label, single-arm, phase II study. Patients with advanced cervical cancer and not previously treated with systemic chemotherapy were enrolled to receive QL1604 plus paclitaxel and cisplatin/carboplatin on day 1 of each 21-day cycle for up to 6 cycles, followed by QL1604 maintenance treatment.
Results:
Forty-six patients were enrolled and the median follow-up duration was 16.5 months. An 84.8% of patients had recurrent disease and 13.0% had stage IVB disease. The objective response rate (ORR) per Response Evaluation Criteria in Advanced Solid Tumors (RECIST) v1.1 was 58.7% (27/46). The immune ORR per immune RECIST was 60.9% (28/46).The median duration of response was 9.6 months (95% confidence interval [CI]=5.5–not estimable). The median progression-free survival was 8.1 months (95% CI=5.7–14.0). Fortyfive (97.8%) patients experienced treatment-related adverse events (TRAEs). The most common grade≥3 TRAEs (>30%) were neutrophil count decrease (50.0%), anemia (32.6%), and white blood cell count decrease (30.4%).
Conclusion
QL1604 plus paclitaxel-cisplatin/carboplatin showed promising antitumor activity and manageable safety profile as first-line treatment in patients with advanced cervical cancer. Programmed cell death protein 1 inhibitor plus chemotherapy may be a potential treatment option for the patient population who have contraindications or can’t tolerate bevacizumab, which needs to be further verified in phase III confirmatory study.
6.QL1604 plus paclitaxel-cisplatin/ carboplatin in patients with recurrent or metastatic cervical cancer:an open-label, single-arm, phase II trial
Cheng FANG ; Yun ZHOU ; Yanling FENG ; Liping HE ; Jinjin YU ; Yuzhi LI ; Mei FENG ; Mei PAN ; Lina ZHAO ; Dihong TANG ; Xiumin LI ; Buzhen TAN ; Ruifang AN ; Xiaohui ZHENG ; Meimei SI ; Baihui ZHANG ; Lingyan LI ; Xiaoyan KANG ; Qi ZHOU ; Jihong LIU
Journal of Gynecologic Oncology 2024;35(6):e77-
Objective:
QL1604 is a highly selective, humanized monoclonal antibody against programmed death protein 1. We assessed the efficacy and safety of QL1604 plus chemotherapy as first-line treatment in patients with advanced cervical cancer.
Methods:
This was a multicenter, open-label, single-arm, phase II study. Patients with advanced cervical cancer and not previously treated with systemic chemotherapy were enrolled to receive QL1604 plus paclitaxel and cisplatin/carboplatin on day 1 of each 21-day cycle for up to 6 cycles, followed by QL1604 maintenance treatment.
Results:
Forty-six patients were enrolled and the median follow-up duration was 16.5 months. An 84.8% of patients had recurrent disease and 13.0% had stage IVB disease. The objective response rate (ORR) per Response Evaluation Criteria in Advanced Solid Tumors (RECIST) v1.1 was 58.7% (27/46). The immune ORR per immune RECIST was 60.9% (28/46).The median duration of response was 9.6 months (95% confidence interval [CI]=5.5–not estimable). The median progression-free survival was 8.1 months (95% CI=5.7–14.0). Fortyfive (97.8%) patients experienced treatment-related adverse events (TRAEs). The most common grade≥3 TRAEs (>30%) were neutrophil count decrease (50.0%), anemia (32.6%), and white blood cell count decrease (30.4%).
Conclusion
QL1604 plus paclitaxel-cisplatin/carboplatin showed promising antitumor activity and manageable safety profile as first-line treatment in patients with advanced cervical cancer. Programmed cell death protein 1 inhibitor plus chemotherapy may be a potential treatment option for the patient population who have contraindications or can’t tolerate bevacizumab, which needs to be further verified in phase III confirmatory study.
7.The chain mediating effect of perceived social support and work-family conflict fit on the relationship between self-efficacy and parenting stress of clinical nurses
Jing SHI ; Jihong FANG ; Jiafeng MIAO ; Jing ZHU ; Limin WANG
Chinese Journal of Practical Nursing 2024;40(26):2013-2021
Objective:To explore the mediation effects of perceived social support and work-family conflict on clinical nurses′ self-efficacy and parenting stress, and to provide theoretical basis for formulating intervention programs for parenting stress.Methods:A total of 631 clinical nurses from 8 grade A hospitals in Anhui Province were selected by convenience sampling method from August to October 2023. A cross-sectional survey was conducted with the general data questionnaire, the Chinese version of Work-Family Behavioral Role Conflict Scale, the Parenting Stress Scale for Clinical Nurses, the Perceptived Social Support Evaluation Scale and the General Self Efficacy Scale to analyze the relationship between perceptive social support, work-family conflict, self-efficacy and parenting stress and the mediating effect.Results:A total of 603 clinical nurses were included, including 9 males and 594 females, aged (35.16 ± 4.59) years. The total scores of work-family conflict, parenting stress, understanding of social support and self-efficacy were (87.10 ± 14.38), (51.00 ± 9.51), (59.91 ± 11.57) and (26.68 ± 6.27) points. The total effect of self-efficacy on parenting stress was - 0.385. The mediating paths of self-efficacy on parenting stress included: self-efficacy→perceived social support→parenting stress; self-efficacy→work-family conflict→parenting stress; self-efficacy→perceived social support→work-family conflict→parenting stress. The three indirect effects accounted for 18.69%, 53.72% and 16.87% of the total effect.Conclusions:Social support and work-family conflict have a chain mediation effect between clinical nurses′self-efficacy and parenting stress. Nursing managers can improve the self-efficacy of clinical nurses and enhance the understanding of social support to help reduce work-family conflict, so as to effectively alleviate the level of child-rearing stress of clinical nurses.
8.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.
9.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.
10.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.

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