1.Phenomics of traditional Chinese medicine 2.0: the integration with digital medicine
Min Xu ; Xinyi Shao ; Donggeng Guo ; Xiaojing Yan ; Lei Wang ; Tao Yang ; Hao LIANG ; Qinghua PENG ; Lingyu Linda Ye ; Haibo Cheng ; Dayue Darrel Duan
Digital Chinese Medicine 2025;8(3):282-299
Abstract
Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.
2.Associations between statins and all-cause mortality and cardiovascular events among peritoneal dialysis patients: A multi-center large-scale cohort study.
Shuang GAO ; Lei NAN ; Xinqiu LI ; Shaomei LI ; Huaying PEI ; Jinghong ZHAO ; Ying ZHANG ; Zibo XIONG ; Yumei LIAO ; Ying LI ; Qiongzhen LIN ; Wenbo HU ; Yulin LI ; Liping DUAN ; Zhaoxia ZHENG ; Gang FU ; Shanshan GUO ; Beiru ZHANG ; Rui YU ; Fuyun SUN ; Xiaoying MA ; Li HAO ; Guiling LIU ; Zhanzheng ZHAO ; Jing XIAO ; Yulan SHEN ; Yong ZHANG ; Xuanyi DU ; Tianrong JI ; Yingli YUE ; Shanshan CHEN ; Zhigang MA ; Yingping LI ; Li ZUO ; Huiping ZHAO ; Xianchao ZHANG ; Xuejian WANG ; Yirong LIU ; Xinying GAO ; Xiaoli CHEN ; Hongyi LI ; Shutong DU ; Cui ZHAO ; Zhonggao XU ; Li ZHANG ; Hongyu CHEN ; Li LI ; Lihua WANG ; Yan YAN ; Yingchun MA ; Yuanyuan WEI ; Jingwei ZHOU ; Yan LI ; Caili WANG ; Jie DONG
Chinese Medical Journal 2025;138(21):2856-2858
3.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*
;
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*
4.Research progress on carrier-free and carrier-supported supramolecular nanosystems of traditional Chinese medicine anti-tumor star molecules
Zi-ye ZANG ; Yao-zhi ZHANG ; Yi-hang ZHAO ; Xin-ru TAN ; Ji-chang WEI ; An-qi XU ; Hong-fei DUAN ; Hong-yan ZHANG ; Peng-long WANG ; Xue-mei HUANG ; Hai-min LEI
Acta Pharmaceutica Sinica 2024;59(4):908-917
Anti-tumor traditional Chinese medicine has a long history of clinic application, in which the star molecules have always been the hotspot of modern drug research, but they are limited by the solubility, stability, targeting, bioactivity or toxicity of the monomer components of traditional Chinese medicine anti-tumor star molecules and other pharmacokinetic problems, which hinders the traditional Chinese medicine anti-tumor star molecules for further clinical translation and application. Currently, the nanosystems prepared by supramolecular technologies such as molecular self-assembly and nanomaterial encapsulation have broader application prospects in improving the anti-tumor effect of active components of traditional Chinese medicine, which has attracted extensive attention from scholars at home and abroad. In this paper, we systematically review the research progress in preparation of supramolecular nano-systems from anti-tumor star molecule of traditional Chinese medicine, and summarize the two major categories and ten small classes of carrier-free and carrier-based supramolecular nanosystems and their research cases, and the future development direction is put forward. The purpose of this paper is to provide reference for the research and clinical transformation of using supramolecular technology to improve the clinical application of anti-tumor star molecule of traditional Chinese medicine.
5.Bibliometric analysis of researches on liver organoids
Canli XU ; Wenxing HE ; Lei WANG ; Fangting WU ; Jiahui WANG ; Xuelin DUAN ; Tiejian ZHAO ; Bin ZHAO ; Yang ZHENG
Chinese Journal of Tissue Engineering Research 2024;28(7):1099-1104
BACKGROUND:In recent years,the development of liver organoids has made it a hot spot in the field of international liver disease research,but there is still no article on the bibliometric analysis of liver organoids. OBJECTIVE:To explore the hot trends in liver organoids in the last 20 years based on bibliometrics and visualization analysis. METHODS:We searched the articles about liver organoids in the Web of Science Core Collection from January 1,2002 to November 12,2022.Origin,Office,and CiteSpace software were used for bibliometrics and visualization analysis.We statistically analyzed the number of annually published articles,countries,institutions,authors,journals,and keywords of the articles by generating charts. RESULTS AND CONCLUSION:The number of articles,citation frequency,institutions and personnel involved in the research about liver organoids showed an overall upward trend in the last 20 years,indicating that the field was growing rapidly and attention was increasing.The USA had published the most papers and had the strongest influence in this field.Although it had invested a lot of time and energy,the number of papers published by a single research institution in the USA was not the highest among many research institutions.China was second only to the USA in the number of publications,with the Chinese Academy of Sciences and Fudan University leading the list.Utrecht University in the Netherlands was the institution with the most publications.Clevers H was the author with the highest number of articles.The article with the highest co-citation frequency was"Long-term culture of genome-stable bipotent stem cells from adult human liver".The main fields of study for liver organoids were Molecular Science,Biology,and Immunology.The most frequently occurring keywords were stem cell,in vitro,and culture.The research hotspots in the liver organoids field were mainly focused on in vitro stem cell three-dimensional culture,differentiation and gene expression.
6.Clinical characteristics and risk factors analysis of dengue fever incidence in Xishuangbanna, Yunnan Province in 2023
Lei CAI ; Shize DUAN ; Wangbin XU ; Dongmei DAI ; Fang YANG ; Man YANG ; Yanhui LI ; Pinghua LIU
Chinese Critical Care Medicine 2024;36(9):917-923
Objective:To analyze the clinical characteristics of dengue fever patients, summarize the course and characteristics of the disease, and analyze the risk factors that affect the condition.Methods:Retrospective collection of general information, clinical symptoms, medical history, laboratory tests, prognosis and other clinical data of dengue fever patients that admitted to Jinghong First People's Hospital and severe dengue fever patients at People's Hospital of Xishuangbanna Dai Autonomous Prefecture from June to December 2023 was conducted using a case report form (CRF). According to the diagnostic criteria of the World Health Organization (WHO), patients were divided into dengue fever group, dengue fever with warning signs group, and severe dengue fever group. The differences in clinical data between different groups of patients were analyzed and compared. Binary multiple factor Logistic regression analysis was used to explore the risk factors affecting the severity of dengue fever in patients. Receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive value of prediction models constructed for various risk factors for severe dengue fever. Subgroup analysis was performed on the prognosis of severe dengue fever patients, and the differences in clinical data between two groups of patients with different prognoses were compared. Binary multivariate Logistic regression analysis was used to explore the risk factors affecting the prognosis of severe dengue fever patients. ROC curve was drawn to analyze the predictive value of prediction models constructed for various risk factors on the prognosis of severe dengue fever patients.Results:A total of 2 264 patients were included, including 499 cases in the dengue fever group, 1 379 cases in the dengue fever with warning signs group, and 386 in the severe dengue fever group (43 deaths and 343 survivors). The most common symptom of dengue fever patients was fever (94.70%), followed by muscle soreness (70.54%), headache (63.12%), fatigue (58.92%), and chills (46.02%). Compared with the dengue fever group and the dengue fever with warning signs group, the ratio of thalassemia and the levels of cardiac troponin (cTnI, cTnT), MB isoenzyme of creatine kinase (CK-MB), and myoglobin were significantly increased in patients with severe dengue fever group, albumin (Alb) was significantly decreased in patients with severe dengue fever group. The levels of cTnT and myoglobin in patients with dengue fever with warning signs group were significantly higher than those in the dengue fever group, and the level of Alb in patients with dengue fever with warning signs group was significantly lower than that in the dengue fever group, the differences were statistically significant (all P < 0.05). Binary multivariate Logistic regression analysis showed that thalassemia [odds ratio ( OR) = 6.214, 95% confidence interval (95% CI) was 2.337-16.524, P < 0.001], Alb ≤ 36 g/L ( OR = 6.297, 95% CI was 4.270-9.286, P < 0.001), and cTnT levels ( OR = 1.008, 95% CI was 1.002-1.015, P = 0.016) were risk factors for severe dengue fever. ROC curve analysis showed that the area under the ROC curve (AUC) for predicting severe dengue fever based on the prediction models constructed for the above risk factors was 0.856, with the best predictive value of 0.067, sensitivity of 67.1%, and specificity of 99.4%. In the subgroup analysis of patients with severe dengue fever, compared with the survival group, the levels of hematocrit (HCT), cTnT, and CK-MB in the death group patients were significantly increased, while the level of Alb was significantly decreased, and the differences were statistically significant. Binary multivariate Logistic regression analysis showed that Alb ( OR = 0.839, 95% CI was 0.755-0.932, P = 0.001), HCT ( OR = 1.086, 95% CI was 1.010-1.168, P = 0.025), elevated troponin level ( OR = 10.119, 95% CI was 2.596-39.440, P < 0.001), and CK-MB ( OR = 1.081, 95% CI was 1.032-1.133, P < 0.001) were risk factors for mortality in patients with severe dengue fever. ROC curve analysis showed that the AUC for predicting death in severe dengue fever patients based on the prediction models constructed for the above risk factors was 0.881, with the best predictive value of 0.113, sensitivity of 75.0%, and specificity of 88.9%. Conclusion:Thalassemia, Alb≤36 g/L, and cTnT level are risk factors for severe dengue fever, while HCT level, Alb level, CK-MB level, and elevated troponin level are risk factors for death in patients with severe dengue fever.
7.Linarin inhibits microglia activation-mediated neuroinflammation and neuronal apoptosis in mouse spinal cord injury by inhibiting the TLR4/NF-κB pathway
Linyu XIAO ; Ting DUAN ; Yongsheng XIA ; Yue CHEN ; Yang SUN ; Yibo XU ; Lei XU ; Xingzhou YAN ; Jianguo HU
Journal of Southern Medical University 2024;44(8):1589-1598
Objective To investigate the mechanism underlying the neuroprotective effect of linarin(LIN)against microglia activation-mediated inflammation and neuronal apoptosis following spinal cord injury(SCI).Methods Fifty C57BL/6J mice(8-10 weeks old)were randomized to receive sham operation,SCI and linarin treatment at 12.5,25,and 50 mg/kg following SCI(n=10).Locomotor function recovery of the SCI mice was assessed using the Basso Mouse Scale,inclined plane test,and footprint analysis,and spinal cord tissue damage and myelination were evaluated using HE and LFB staining.Nissl staining,immunofluorescence assay and Western blotting were used to observe surviving anterior horn motor neurons in injured spinal cord tissue.In cultured BV2 cells,the effects of linarin against lipopolysaccharide(LPS)-induced microglia activation,inflammatory factor release and signaling pathway changes were assessed with immunofluorescence staining,Western blotting,RT-qPCR,and ELISA.In a BV2 and HT22 cell co-culture system,Western blotting was performed to examine the effect of linarin against HT22 cell apoptosis mediated by LPS-induced microglia activation.Results Linarin treatment significantly improved locomotor function(P<0.05),reduced spinal cord damage area,increased spinal cord myelination,and increased the number of motor neurons in the anterior horn of the SCI mice(P<0.05).In both SCI mice and cultured BV2 cells,linarin effectively inhibited glial cell activation and suppressed the release of iNOS,COX-2,TNF-α,IL-6,and IL-1β,resulting also in reduced neuronal apoptosis in SCI mice(P<0.05).Western blotting suggested that linarin-induced microglial activation inhibition was mediated by inhibition of the TLR4/NF-κB signaling pathway.In the cell co-culture experiments,linarin treatment significantly decreased inflammation-mediated apoptosis of HT22 cells(P<0.05).Conclusion The neuroprotective effect of linarin is medicated by inhibition of microglia activation via suppressing the TLR4/NF-κB signaling pathway,which mitigates neural inflammation and reduce neuronal apoptosis to enhance motor function of the SCI mice.
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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