1.rTMS Improves Cognitive Function and Brain Network Connectivity in Patients With Alzheimer’s Disease
Gui-Zhi XU ; Lin LIU ; Miao-Miao GUO ; Tian WANG ; Jiao-Jiao GAO ; Yong JI ; Pan WANG
Progress in Biochemistry and Biophysics 2025;52(8):2131-2145
ObjectiveRepetitive transcranial magnetic stimulation (rTMS) has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease (AD), but the neurobiological mechanisms linking synaptic pathology, neural oscillatory dynamics, and brain network reorganization remain unclear. This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments, molecular profiling, and neurophysiological monitoring. MethodsIn this prospective double-blind trial, 12 AD patients underwent a 14-day protocol of 20 Hz rTMS, with comprehensive multimodal assessments performed pre- and post-intervention. Cognitive functioning was quantified using the mini-mental state examination (MMSE) and Montreal cognitive assessment (MOCA), while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living (ADL) scale and combined neuropsychiatric inventory (NPI)-Hamilton depression rating scale (HAMD). Peripheral blood biomarkers, specifically Aβ1-40 and phosphorylated tau (p-tau181), were analyzed to investigate the effects of rTMS on molecular metabolism. Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients, while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization. Furthermore, systematic assessment of correlations between cognitive scale scores, blood biomarkers, and network characteristics was performed to elucidate cross-modal therapeutic associations. ResultsClinically, MMSE and MOCA scores improved significantly (P<0.05). Biomarker showed that Aβ1-40 level increased (P<0.05), contrasting with p-tau181 reduction. Moreover, the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores. Post-intervention analyses revealed significant modulations in oscillatory power, characterized by pronounced reductions in delta (P<0.05) and theta bands (P<0.05), while concurrent enhancements were observed in alpha, beta, and gamma band activities (all P<0.05). Network analysis revealed frequency-specific reorganization: clustering coefficients were significantly decreased in delta, theta, and alpha bands (P<0.05), while global efficiency improvement was exclusively detected in the delta band (P<0.05). The alpha band demonstrated concurrent increases in average nodal degree (P<0.05) and characteristic path length reduction (P<0.05). Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181. Additionally, the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band. However, the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands. Conclusion20 Hz rTMS targeting dorsolateral prefrontal cortex (DLPFC) significantly improves cognitive function and enhances the metabolic clearance of β-amyloid and tau proteins in AD patients. This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation, which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks. These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales, blood biomarkers, and EEG——in understanding and monitoring the progression of AD. This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.
2.Road traffic mortality in Zunyi city, China: A 10 - year data analysis (2013-2022).
Tian-Jing SUN ; Xiao-Fei HUANG ; Fang-Ke XIE ; Ji ZHANG ; Xu-Heng JIANG ; An-Yong YU
Chinese Journal of Traumatology 2025;28(2):145-150
PURPOSE:
The study aimed to examine the pattern of motorization and the mortality rate related to road traffic crashes in Zunyi (a city in northern Guizhou province of China) from 2013 to 2022, and to identify the epidemiological characteristics of these crashes with to provide insights that could help improve road safety.
METHODS:
Data were obtained from the Zunyi traffic management data platform, and the mortality rates were calculated. We deployed various analytical methods, including descriptive analysis, Chi-square test or Fisher's exact test for categorical variables, circular distribution map analysis, and Rayleigh test to characterize the traits of road traffic crashes in the region.
RESULTS:
During the 10-year study period, 7488 people died due to road traffic accidents, with males accounting for 70.4% and females 29.6% (χ2 = 101.97, p < 0.001). The mortality rate increased from 7.80 deaths per 100,000 people in 2013 to 10.70 deaths per 100,000 people in 2016, but then decreased to 9.54 deaths per 100,000 people in 2019. A notable finding was that the death rate per 10,000 vehicles declined from 16.09 deaths per 10,000 vehicles in 2013 to 5.48 deaths per 10,000 vehicles in 2022. The study also found that vulnerable road users represented nearly half (48.76%) of all accident fatalities, and unlicensed or inexperienced driving contributed significantly to the occurrence of road traffic accidents.
CONCLUSION
Although the number of road traffic accidents in Zunyi has decreased, there are still some critical issues that need to be addressed, particularly for vulnerable road users and unlicensed drivers. Our results highlight the need for targeted interventions to address the specific risk factors of road traffic crashes, particularly those affecting vulnerable road users and drivers without sufficient experience or license.
Humans
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Accidents, Traffic/statistics & numerical data*
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China/epidemiology*
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Male
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Female
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Adult
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Middle Aged
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Aged
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Adolescent
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Young Adult
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Child
3.Nonsurgical Treatment of Chronic Subdural Hematoma Patients with Chinese Medicine: Case Report Series.
Kang-Ning LI ; Wei-Ming LIU ; Ying-Zhi HOU ; Run-Fa TIAN ; Shuo ZHANG ; Liang WU ; Long XU ; Jia-Ji QIU ; Yan-Ping TONG ; Tao YANG ; Yong-Ping FAN
Chinese journal of integrative medicine 2025;31(10):937-941
4.Longitudinal extrauterine growth restriction in extremely preterm infants: current status and prediction model
Xiaofang HUANG ; Qi FENG ; Shuaijun LI ; Xiuying TIAN ; Yong JI ; Ying ZHOU ; Bo TIAN ; Yuemei LI ; Wei GUO ; Shufen ZHAI ; Haiying HE ; Xia LIU ; Rongxiu ZHENG ; Shasha FAN ; Li MA ; Hongyun WANG ; Xiaoying WANG ; Shanyamei HUANG ; Jinyu LI ; Hua XIE ; Xiaoxiang LI ; Pingping ZHANG ; Hua MEI ; Yanju HU ; Ming YANG ; Lu CHEN ; Yajing LI ; Xiaohong GU ; Shengshun QUE ; Xiaoxian YAN ; Haijuan WANG ; Lixia SUN ; Liang ZHANG ; Jiuye GUO
Chinese Journal of Neonatology 2024;39(3):136-144
Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.
5.Mannitol inhibits the proliferation of neural stem cell by a p38 mitogen-activated protein kinase-dependent signaling pathway
Hai-Zhen DUAN ; Xin ZHOU ; Quan HU ; Meng-Long LIU ; Shu-Hong WANG ; Ji ZHANG ; Xu-Heng JIANG ; Tian-Xi ZHANG ; An-Yong YU
Chinese Journal of Traumatology 2024;27(1):42-52
Purpose::Mannitol is one of the first-line drugs for reducing cerebral edema through increasing the extracellular osmotic pressure. However, long-term administration of mannitol in the treatment of cerebral edema triggers damage to neurons and astrocytes. Given that neural stem cell (NSC) is a subpopulation of main regenerative cells in the central nervous system after injury, the effect of mannitol on NSC is still elusive. The present study aims to elucidate the role of mannitol in NSC proliferation.Methods::C57 mice were derived from the animal house of Zunyi Medical University. A total of 15 pregnant mice were employed for the purpose of isolating NSCs in this investigation. Initially, mouse primary NSCs were isolated from the embryonic cortex of mice and subsequently identified through immunofluorescence staining. In order to investigate the impact of mannitol on NSC proliferation, both cell counting kit-8 assays and neurospheres formation assays were conducted. The in vitro effects of mannitol were examined at various doses and time points. In order to elucidate the role of Aquaporin 4 (AQP4) in the suppressive effect of mannitol on NSC proliferation, various assays including reverse transcription polymerase chain reaction, western blotting, and immunocytochemistry were conducted on control and mannitol-treated groups. Additionally, the phosphorylated p38 (p-p38) was examined to explore the potential mechanism underlying the inhibitory effect of mannitol on NSC proliferation. Finally, to further confirm the involvement of the p38 mitogen-activated protein kinase-dependent (MAPK) signaling pathway in the observed inhibition of NSC proliferation by mannitol, SB203580 was employed. All data were analyzed using SPSS 20.0 software (SPSS, Inc., Chicago, IL). The statistical analysis among multiple comparisons was performed using one-way analysis of variance (ANOVA), followed by Turkey's post hoc test in case of the data following a normal distribution using a Shapiro-Wilk normality test. Comparisons between 2 groups were determined using Student's t-test, if the data exhibited a normal distribution using a Shapiro-Wilk normality test. Meanwhile, data were shown as median and interquartile range and analyzed using the Mann-Whitney U test, if the data failed the normality test. A p < 0.05 was considered as significant difference. Results::Primary NSC were isolated from the mice, and the characteristics were identified using immunostaining analysis. Thereafter, the results indicated that mannitol held the capability of inhibiting NSC proliferation in a dose-dependent and time-dependent manner using cell counting kit-8, neurospheres formation, and immunostaining of Nestin and Ki67 assays. During the process of mannitol suppressing NSC proliferation, the expression of AQP4 mRNA and protein was downregulated, while the gene expression of p-p38 was elevated by reverse transcription polymerase chain reaction, immunostaining, and western blotting assays. Subsequently, the administration of SB203580, one of the p38 MAPK signaling pathway inhibitors, partially abrogated this inhibitory effect resulting from mannitol, supporting the fact that the p38 MAPK signaling pathway participated in curbing NSC proliferation induced by mannitol.Conclusions::Mannitol inhibits NSC proliferation through downregulating AQP4, while upregulating the expression of p-p38 MAPK.
6.CT radiomics for differentiating spinal bone island and osteoblastic bone metastases
Xin WEN ; Liping ZUO ; Yong WANG ; Ziyu TIAN ; Fei LU ; Shuo SHI ; Lingyu CHANG ; Yu JI ; Ran ZHANG ; Dexin YU
Chinese Journal of Medical Imaging Technology 2024;40(5):758-763
Objective To observe the value of CT radiomics for differentiating spinal bone islands(BI)and osteoblastic metastases(OBM).Methods Data of 109 BI lesions in 98 patients and 282 OBM lesions in 158 patients(including 103 OBM in 48 lung cancer cases,86 OBM in 52 breast cancer cases and 93 OBM in 58 prostate cancer cases)from 3 medical institutions were retrospectively analyzed.Data obtained from institution 1 were used as the internal dataset and divided into internal training set and internal validation set at a ratio of 7∶3,from institution 2 and 3 were used as external dataset.All datasets were divided into female data subset(including OBM of female lung cancer and breast cancer)and male data subset(including OBM of male lung cancer and prostate cancer).Radiomics features were extracted and screened to construct 3 different support vector machine(SVM)models,including model1 for distinguishing BI and OBM,model2 for differentiating OBM of female lung cancer and breast cancer,and model3 for differentiating OBM of male lung cancer and prostate cancer.Diagnostic efficacy of model1,CT value alone and 3 physicians(A,B,C)for distinguishing BI and OBM were assessed,as well as differentiating efficacy for different OBM of model2 and model3.Receiver operating characteristic(ROC)curves were drawn,and area under the curves(AUC)were calculated and compared.The differential diagnostic efficacy of model2 and model3 were also assessed with ROC analysis and AUC.Results AUC of model1 for distinguishing spinal OBM from BI in internal training set,internal validation set and external dataset was 0.99,0.98 and 0.86,respectively.In internal training set,model1 had higher AUC for distinguishing BI and OBM than that of physician A(AUC=0.78),B(AUC=0.87)and C(AUC=0.93)as well as that of mean CT value(AUC=0.78,all P<0.05).AUC in internal training set,internal validation set and external dataset of model2 for identifying female lung cancer and breast cancer OBM was 0.79,0.75 and 0.73,respectively,of model3 for discriminating male lung cancer from prostate cancer OBM was 0.77,0.74 and 0.77,respectively.Conclusion CT radiomics SVM model might reliablely distinguish OBM and BI.
7.Factors for low libido in male patients with sexual dysfunction
Qiu-Chen LÜ ; Rui WANG ; Zu-Long WANG ; Tian-Ji ZHANG ; Tao ZHENG ; Kun-Long LÜ ; Yong-Hao NAN
National Journal of Andrology 2024;30(8):734-737
Objective:To analyze the factors for low libido in male patients with sexual dysfunction and provide some evidence for the clinical diagnosis and treatment of the condition.Methods:We retrospectively analyzed the clinical data on 111 cases of sex-ual dysfunction(including disorders in erection,ejaculation or libido)treated in the Zhengzhou University First Hospital from June to September 2023.According to the patients'complaints of low libido or accompanied symptoms,we divided them into a normal libido group(n=68)and a low libido(n=43),obtained their scores on IIEF-5,Premature Ejaculation Diagnostic Tool(PEDT),13-1-tem Self-Rating Libido Scale for Males(SRLS-M),Patients'Health Questionnaire-9(PHQ-9)and General Anxiety Disorder-7(GAD-7),examined the levels of the sexual hormones FSH,LH,PRL,T,free testosterone(fT),E2,?insulin-like growth factor 1(IGF-1)and growth hormone(GH),compared the basic parameters between the two groups,and analyzed their correlation with the libido values.Results:The IIEF-5,PEDT and libido scores and IGF-1 level were significantly higher and the GAD-7 score remark-ably lower in the normal than in the low libido group(P<0.05),but no statistically significant differences were observed between the two groups in the PHQ-9 score and the levels FSH,LH,PRL,T,fT,E2,T/E2 and GH(P>0.05).The libido value was correla-ted positively with the I1EF-5(r=0.28,P<0.01)and PEDT scores(r=0.29,P<0.01)and IGF-1 level(r=0.23,P<0.05),but negatively with the GAD-7 score(r=-0.21,P<0.05).Conclusion:Low libido results from multiple factors,which cannot be fully explained by sexual hormone levels but is closely related to the decreased level of IGF-1 and severity of ED and anxiety.
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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