1.Mechanisms and Strategy of Traditional Chinese Medicine in Treatment of Ischemic Stroke: A Review
Maodi WENG ; Qiuyan CHEN ; Kai WANG ; Yun LUO ; Xiaobo SUN
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(1):310-316
Ischemic stroke (IS) represents a major global health challenge with complex pathological mechanisms. Although modern therapies such as intravenous thrombolysis and endovascular thrombectomy have advanced, their application remains constrained by narrow therapeutic time windows, hemorrhagic risks, and uneven distribution of medical resources. Traditional Chinese medicine (TCM) demonstrates unique value in the prevention and treatment of IS, owing to its multi-component, multi-target, and holistic regulatory characteristics. This review summarized the molecular mechanisms by which active ingredients and compound formulations of TCM exert therapeutic effects against IS through the regulation of inflammatory responses, oxidative stress, excitatory toxicity, apoptosis, and autophagy. Studies have indicated that components such as curcumin, baicalin, and astragaloside Ⅳ inhibit microglial activation and the nucleotide-binding oligomerization domain (NOD)-like receptor protein 3 (NLRP3) inflammasome to attenuate neuroinflammation, activate the nuclear factor erythroid 2-related factor 2(Nrf2)/heme oxygenase-1 (HO-1) pathway to alleviate oxidative stress, modulate glutamate receptor function to counteract excitatory toxicity, and regulate the B-cell lymphoma 2(Bcl-2)/Bcl-2-associated X protein (Bax), cysteine aspartate-specific protease (Caspase), and phosphatidylinositol 3 kinases (PI3K)/protein kinase B (Akt) signaling pathways to suppress neuronal apoptosis. Recent research has further revealed that TCM can modulate ferroptosis by targeting key proteins glutathione peroxidase 4 (GPX4) and acyl-coenzyme A synthetase long-chain family member 4 (ACSL4) to maintain iron homeostasis, intervene in the "microbiota-gut-brain axis" to ameliorate dysbiosis and reduce neuroinflammation, utilize exosomes for brain-targeted drug delivery, and influence neural repair processes through epigenetic regulation. Furthermore, the review discussed the integrated mechanisms of compound formulations, such as Buyang Huanwu Decoction, in improving cerebral microcirculation and promoting neurovascular remodeling via multi-component synergy. It also analyzed the strategy and advantages of integrating TCM with Western medicine for IS treatment, providing a novel theoretical foundation and research directions for future investigations and clinical translation of TCM in IS management.
2.Risk factors associated with postoperative adjuvant therapy for resectable esophageal squamous cell carcinoma
Teng ZENG ; Rui HE ; Xiaobo CHEN ; Chao MING ; Guangqiang ZHAO
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(02):326-332
The benefit of postoperative adjuvant therapy for patients with resectable esophageal squamous cell carcinoma (ESCC) is not yet supported by high-level evidence. This review analyzes the role of adjuvant therapy by examining the discrepancy between clinical needs and guidelines, its historical evolution, recent advances in high-risk factors, and future outlooks. We provide a detailed discussion of high-risk factors used for patient selection, including lymph node positivity, and for node-negative patients, features such as tumor length, location, T stage, extent of lymph node dissection, differentiation, vascular and neural invasion, laboratory indices, and molecular markers. The goal is to inform the development of individualized precision treatment strategies for resectable ESCC.
3.Association between ambient particulate matter exposure and risk of benign prostatic hyperplasia in middle-aged and older men: A longitudinal cohort study based on CHARLS
Hanxiao HU ; Chuchu LIU ; Yuyuan HU ; Jiali CHEN ; Lingyi WANG ; Xiaobo LIU ; Yue WU
Journal of Environmental and Occupational Medicine 2026;43(5):630-636
Background Benign prostatic hyperplasia (BPH) is a common chronic urinary disease in middle-aged and older men, yet the impact of long-term exposure to atmospheric particulate matter (PM) on its pathogenesis remains unclear. Objective To investigate the association between PM exposure and the risk of incident BPH in middle-aged and older men. Methods Based on four waves of follow-up data (2011–2018) from the China Health and Retirement Longitudinal Study (CHARLS), 4766 participants were enrolled. Robust Poisson regression models were employed to assess the association between exposure to PM (PM1, PM2.5, and PM10) and the risk of incident BPH. Relative risks (RR) and their corresponding 95% confidence intervals (95%CI) were calculated. Dose-response relationships were fitted using restricted cubic splines (RCS). Subgroup analyses were performed to explore potential effect modifications, and multiple imputation was used to handle missing data. Results Over a mean follow-up of 6 years, 914 incident BPH cases were identified among the4766 participants (cumulative incidence: 19.18%). After adjusting for confounders, each 10 μg·m−3 increase in PM1, PM2.5, and PM10 concentrations was associated with a 13.1% (RR=1.131, 95%CI: 1.063, 1.203), 8.5% (RR=1.085, 95%CI: 1.050, 1.122), and 5.1% (RR=1.051, 95%CI: 1.034, 1.069) increased risk of BPH, respectively. RCS analysis showed that no nonlinear relationship was found between PM1 and PM2.5 and the risk of BPH (P>0.05); however, a nonlinear association was observed for PM10 (P=0.03), with the risk increment slowing beyond 100 μg·m−3. Subgroup and sensitivity analyses confirmed the robustness of these findings. Conclusion Long-term exposure to ambient particulate matter may be associated with an increased risk of incident BPH in middle-aged and older men.
4.Association between ambient particulate matter exposure and risk of benign prostatic hyperplasia in middle-aged and older men: A longitudinal cohort study based on CHARLS
Hanxiao HU ; Chuchu LIU ; Yuyuan HU ; Jiali CHEN ; Lingyi WANG ; Xiaobo LIU ; Yue WU
Journal of Environmental and Occupational Medicine 2026;43(5):630-636
Background Benign prostatic hyperplasia (BPH) is a common chronic urinary disease in middle-aged and older men, yet the impact of long-term exposure to atmospheric particulate matter (PM) on its pathogenesis remains unclear. Objective To investigate the association between PM exposure and the risk of incident BPH in middle-aged and older men. Methods Based on four waves of follow-up data (2011–2018) from the China Health and Retirement Longitudinal Study (CHARLS), 4766 participants were enrolled. Robust Poisson regression models were employed to assess the association between exposure to PM (PM1, PM2.5, and PM10) and the risk of incident BPH. Relative risks (RR) and their corresponding 95% confidence intervals (95%CI) were calculated. Dose-response relationships were fitted using restricted cubic splines (RCS). Subgroup analyses were performed to explore potential effect modifications, and multiple imputation was used to handle missing data. Results Over a mean follow-up of 6 years, 914 incident BPH cases were identified among the4766 participants (cumulative incidence: 19.18%). After adjusting for confounders, each 10 μg·m−3 increase in PM1, PM2.5, and PM10 concentrations was associated with a 13.1% (RR=1.131, 95%CI: 1.063, 1.203), 8.5% (RR=1.085, 95%CI: 1.050, 1.122), and 5.1% (RR=1.051, 95%CI: 1.034, 1.069) increased risk of BPH, respectively. RCS analysis showed that no nonlinear relationship was found between PM1 and PM2.5 and the risk of BPH (P>0.05); however, a nonlinear association was observed for PM10 (P=0.03), with the risk increment slowing beyond 100 μg·m−3. Subgroup and sensitivity analyses confirmed the robustness of these findings. Conclusion Long-term exposure to ambient particulate matter may be associated with an increased risk of incident BPH in middle-aged and older men.
5.Machine learning model based on contrast enhanced CT images for predicting mitotic index in gastrointestinal stromal tumors: a dual-center study
Wenjun DIAO ; Xiaobo CHEN ; Ximing WANG ; Hexiang WANG ; Xingyu CHEN ; Yanqi HUANG ; Zaiyi LIU
Chinese Journal of Radiology 2025;59(5):549-557
Objective:To develop and validate machine learning-based radiomics models using preoperative CT images for individualized prediction of mitotic index (MI) in patients with gastrointestinal stromal tumors (GIST).Methods:The study was a case-control study. The data of 348 GIST patients confirmed by pathology were retrospectively collected from two independent medical centers: the Affiliated Hospital of Qingdao University (center 1) and Shandong Provincial Hospital Affiliated to Shandong First Medical University (center 2), covering the period from January 2013 to June 2018. Patients from center 1 were divided into a training cohort (176 cases) and an internal validation cohort (75 cases) at a ratio of 7∶3 using random sampling. Patients from center 2 served as an independent external validation cohort (97 cases). The primary endpoint was MI, categorized into high MI (145 cases) and low MI (203 cases) groups. Radiomic features were extracted from the portal venous phase images of preoperative contrast-enhanced CT scans. Five machine learning algorithms, including logistic regression, support vector machine, random forest, decision tree, and extreme gradient boosting (XGBoost),were employed to construct MI prediction models. The optimal model was identified using receiver operating characteristic curves. An individualized prediction model was developed by integrating the the optimal machine learning model combined with selected independent clinical factors, and the importance of features was visualized using Shapley Additive Explanation (SHAP) analysis. Patients were followed up, and Kaplan-Meier curves along with log-rank tests were used to evaluate recurrence-free survival (RFS) differences between the predicted high MI and low MI groups.Results:Among the five constructed machine learning models, the XGBoost model demonstrated the best predictive performance, with area under the curve (AUC) of 0.809 (95% CI 0.738-0.872), 0.693 (95% CI 0.571-0.809), and 0.718 (95% CI 0.605-0.822) in the training cohort, internal validation cohort, and external validation cohort, respectively. An individualized prediction model combining the XGBoost model with independent clinical factors (tumor location and tumor size) was developed. The model achieved AUC of 0.843 (95% CI 0.785-0.899), 0.791 (95% CI 0.680-0.894), and 0.777 (95% CI 0.678-0.861) in the training cohort, internal validation cohort, and external validation cohort, respectively. SHAP analysis indicated that radiomic features had the highest predictive impact. In both the training cohort and internal validation cohort, the RFS of patients predicted to be in the high MI group was lower than that of the low MI group, with statistically significant differences ( χ2=14.58, 9.52, both P<0.001). However, there was no statistically significant difference in RFS in the external validation set ( χ2=6.18, P=0.080). Conclusions:The optimal XGBoost model based on radiomic features extracted from preoperative portal venous phase CT images, when combined with clinical factors, can effectively predict the MI of GIST patients.
6.Cerebrospinal fluid flow dynamics and volume changes of pulsatile tinnitus patients caused by sigmoid sinus wall dehiscence based on MRI
Lanyue CHEN ; Wei LI ; Xiaobo MA ; Xiaoxia QU ; Mengdi ZHOU ; Xiwen WANG ; Shanbin SUN ; Zhaohui LIU
Chinese Journal of Radiology 2025;59(8):917-922
Objective:To evaluate cerebrospinal fluid (CSF) flow dynamics and volume changes of pulsatile tinnitus (PT) patients induced by sigmoid sinus wall dehiscence (SSWD) using MRI.Methods:This was a cross-sectional study. Totally 55 SSWD-PT patients, and 35 age- and sex-matched healthy controls were prospectively enrolled at Beijing Tongren Hospital, Capital Medical University from October 2019 to September 2023. The CSF at the midbrain aqueduct level was analyzed based on phase-contrast MRI to obtain the flow dynamics information. Based on T 1-weighted turbo field echo sequence, the CSF was segmented and the volume of CSF was calculated using ITK-SNAP software. The Mann-Whitney U test was used to compare the differences of each parameter between the two groups. Binary logistic regression was used to analyze the parameters with statistically significant differences to obtain the independent influencing factors of SSWD-PT and establish the combined parameters. Receiver operating characteristic curve analysis was used to evaluate the efficacy of diagnosing SSWD-PT. Results:Compared with controls, the SSWD-PT group showed significantly decreased mean flux (MF), mean velocity, peak velocity( P<0.05), and significantly increased regurgitant fraction (RF), CSF volume ( P<0.05). No significant differences were observed in forward flow volume, backward flow volume, and stroke volume ( P>0.05). The logistic regression results showed that MF ( OR=0.497, 95% CI 0.305-0.808, P=0.005) and RF ( OR=1.809, 95% CI 1.040-3.147, P=0.036) were independent influencing factors of SSWD-PT. The area under the curve (AUC) of MF and RF for diagnosing SSWD-PT were 0.641 (95% CI 0.517-0.766) and 0.675 (95% CI 0.564-0.786), respectively. The AUC of the combination of MF and RF was 0.724 (95% CI 0.614-0.833). Conclusions:SSWD-PT patients have abnormal changes in CSF flow dynamics and volume. The MF and RF demonstrate moderate diagnostic value for diagnosing SSWD-PT.
7.Impact factors of vascular heat sink effect during in vitro microwave ablation of porcine lung
Zenan CHEN ; Zhongliang ZHANG ; Sibin WANG ; Xinyuan GUO ; Jing ZHANG ; Xiaobo ZHANG ; Xiaofeng HE ; Liangliang MENG ; Xin ZHANG ; Yingtian WEI ; Yueyong XIAO ; Qun NAN ; Xiao ZHANG
Chinese Journal of Medical Imaging Technology 2025;41(3):383-388
Objective To observe the impact factors of vascular heat sink effect during in vitro microwave ablation(MWA)of porcine lung.Methods Simulation models were established using in vitro porcine lung tissue blocks based on isobaric inflation with an air pump and cyclic perfusion of duck blood with a glass tube and peristaltic pump,etc.MWA was performed under 8 different combining conditions(vessel diameter of 3 or 5 mm,blood perfusion of 30 or 50 cm/s,as well as distance between vessel and ablation antenna of 5 or 10 mm)each for 3 times.The highest temperature TV on vessel side and TC on control side during MWA,and ablation depth DV on vessel side and DC on control side after MWA were recorded.Multi-factor linear regression equations were constructed based on simulated vessel diameters,blood perfusion and distance between vessel and ablation antenna,and the impact factors of|TC-TV|and|DC-DV|were screened,respectively.Results Simulated vessel diameter showed linear positive correlation with both|TC-TV|and|DC-DV|(both P<0.001).Simulated distance between vessel and ablation antenna showed linear negative correlation with both|TC-TV|and|DC-DV|(both P<0.001),and the latter had more obvious impact on vascular heat sink effect than the former.Meanwhile,no significant linear relationship was found between simulated blood perfusion and|TC-TV|nor|DC-DV|(both P>0.05).Conclusion Simulated vessel diameter and distance between vessel and ablation antenna were both impact factors of vascular heat sink effect during in vitro MWA of porcine lung,and the latter was more influential,whereas simulated blood perfusion showed no significant impact on it.
8.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
9.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; 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 ; 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 ; Wenhui HUANG ; 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 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
10.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

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