OBJECTIVE To evaluate the cost-effectiveness of cefiderocol versus best available therapy （BAT） or standard-of- care （SOC） for the treatment of confirmed or suspected carbapenem-resistant Gram-negative bacterial （CRGNB） serious infections from the perspective of the Chinese healthcare system， and to explore its reasonable pricing. METHODS A decision tree model was constructed based on data from two phase Ⅲ clinical trials （CREDIBLE-CR and GAME CHANGER） to simulate the cost- effectiveness of cefiderocol in two scenarios： salvage therapy for confirmed CRGNB infection （scenario 1） and empirical therapy for suspected CRGNB infection （scenario 2）. The primary outcome measure was the incremental cost-effectiveness ratio （ICER）. The willingness-to-pay （WTP） was set at 1 to 3 times China’s per capita GDP in 2024. To verify the robustness of the results， one- way and probabilistic sensitivity analyses were conducted， and based on these， a reasonable price range for cefiderocol in the Chinese market was explored. RESULTS The results for scenario 1 showed that the clinical cure rate in the cefiderocol group was higher than that in the BAT group （47.50% vs. 34.21%）， but its ICER was 415 065.03 yuan per cured case， exceeding three times China’s GDP per capita. Scenario 2 revealed that the ICER for cefiderocol relative to SOC was as high as 1 362 446.16 yuan per cured case， far exceeding the WTP. Sensitivity analysis indicated that the treatment duration and price of cefiderocol were key factors affecting its cost-effectiveness. In the two scenarios described above， the unit price of cefiderocol must fall below 683.47 and 242.00 yuan/g， respectively， to be considered cost-effective. CONCLUSIONS Based on the current market price， cefiderocol lacks sufficient cost-effectiveness for treating confirmed or suspected CRGNB serious infections within China’s healthcare system. To improve its accessibility， price negotiations or a tiered medical insurance payment strategy are required.

BackgroundEmotional disorders in adolescents have emerged as a prominent issue in recent years. Current mainstream clinical assessment approaches for such conditions predominantly rely on interviews and rating scales， which are limited by inherent drawbacks such as high subjectivity and recall bias. Accordingly， there exists an urgent clinical need for the development of objective， quantifiable auxiliary diagnostic tools.In previous studies， frontal electroencephalography （EEG） has demonstrated significant value in assessing depressive and anxiety. However， the lack of standardized quantitative metrics and intuitive visual analytical approaches has severely restricted clinical interpretability of EEG data and diminished patient engagement. To address these key limitations， the present study proposes an innovative analytical framework that converts frontal EEG signals into quantifiable visual metrics to enhance clinical comprehension and acceptance. ObjectiveTo explore the value of frontal EEG in assessing anxiety， depression， and sleep quality in adolescents with emotional disorders， with the aim of providing objective auxiliary tools for clinical diagnosis and assessment of adolescents with emotional disorders. MethodsThis cross-sectional study recruited 105 adolescents aged 12-18 years who visited the outpatient department of a specialized mental hospital in Beijing from April 2023 to April 2024. All participants met the diagnostic criteria for mood （affective） disorders or anxiety disorders in the International Classification of Diseases， tenth edition （ICD-10）. Frontal EEG signals were collected within a big data analytics-driven framework and further processed by EEG system to generate six quantitative cerebral function indices， namely brain load， tension and excitement， emotional stress， sleepiness index， cerebral vitality， and cerebral fatigue. In addition， validated standardized scales， including the Self-rating Anxiety Scale （SAS）， the Self-rating Depression Scale （SDS）， and the Pittsburgh Sleep Quality Index （PSQI）， were administered for anxiety， depressive symptoms， and sleep quality， respectively. ResultsIn adolescent patients with emotional disorders， the SAS score exhibited significant positive correlations with brain load （r_s=0.328， P<0.01）， emotional stress （r_s=0.341， P<0.01）， and cerebral fatigue （r_s=0.286， P<0.01）. The SDS score was positively correlated with brain load （r_s=0.275， P<0.01）， emotional stress （r_s=0.241， P<0.05）， and cerebral fatigue （r_s=0.311， P<0.01）， while showing a significant negative correlation with cerebral vitality （r_s=-0.212， P<0.05）. Additionally， the PSQI total score demonstrated positive correlations with brain load （r_s=0.340， P<0.01）， emotional stress （r_s=0.322， P<0.01）， and cerebral fatigue （r_s=0.229， P<0.05）. ConclusionFrontal EEG-derived indices， including brain load， emotional stress， cerebral fatigue and cerebral vitality， may serve as objective markers for reflecting anxiety， depression， and sleep quality in adolescents with emotional disorders. ［Funded by Beijing High level Innovation and Entrepreneurship Talent Support Program （number， 202504841041）； Horizontal Joint Project］

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

Background Per- and polyfluoroalkyl substances (PFAS) are a class of persistent organic pollutants widely used in various products, leading to population exposure and long-term accumulation. At present, there is a lack of research on the relationships between pre-pregnancy PFAS and menstrual characteristics among women undergoing assisted reproductive technology (ART) in China. Objective To explore the relationships between pre-pregnancy PFAS exposure among women undergoing ART and menstrual characteristics prior to assisted reproductive treatment. Methods This study employed a cross-sectional research design, recruiting women undergoing ART treatment at the Reproductive Clinic of the International Peace Maternity & Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, from 2017 to 2020 as study participants. Ultra-high-performance liquid chromatography-tandem mass spectrometry was used to detect 42 types of PFAS in pre-pregnancy serum samples. Questionnaires were administered to collect information on demographic characteristics, lifestyle habits, and menstrual characteristics (average menstrual cycle length, average menstrual period length, menstrual irregularities, and menstrual bleeding volume) of women undergoing ART. Multiple linear regression, binary logistic regression, and multinomial logistic regression analyses were performed to investigate the relationships between individual PFAS exposure before pregnancy and menstrual characteristics among ART women. Additionally, weighted quantile sum (WQS) model was applied to analyze the association between PFAS mixtures and menstrual characteristics. Results In the pre-pregnancy serum samples of the study population, 15 PFAS were detected in more than 60% of the samples, including perfluoroheptanoic acid (PFHpA), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUnDA), perfluorododecanoic acid (PFDoDA), perfluorobutanesulfonic acid (PFBS), perfluorohexanesulfonic acid (PFHxS), perfluoroheptanesulfonic acid (PFHpS), perfluorooctanesulfonic acid (PFOS), 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA), 8:2 chlorinated polyfluorinated ether sulfonate (8:2 Cl-PFESA), perfluoro-2-propoxypropanoic acid (HFPO-DA), perfluoro-2-methoxyacetic acid (PFMOAA), and perfluoro-(3,5,7,9,11-pentaoxadodecanoic) acid (PFO5DoDA). Among them, PFOA had the highest median concentration of 9.160 ng·mL⁻¹. The single PFAS exposure analysis revealed a positive correlation between PFAS and irregular menstrual cycles. Specifically, for every natural-log unit (e) increase in PFOA, PFBS, or PFHxS level, the incidence of irregular menstrual cycles increased by 57%, 42%, or 39%, respectively. Most PFAS were positively correlated with the average number of menstrual cycle days, such as PFHpA (b=1.08, 95%CI: 0.11, 2.05), PFOA (b=1.69, 95%CI: 0.39, 3.00), PFBS (b=1.23, 95%CI: 0.25, 2.22), PFHxS (b=1.47, 95%CI: 0.61, 2.32), PFHpS (b=1.48, 95%CI: 0.35, 2.61), and 6:2 Cl-PFESA (b=0.90, 95%CI: 0.08, 1.72). Furthermore, levels of PFHpA (OR=1.39, 95%CI: 1.06, 1.82), PFOA (OR=1.58, 95%CI: 1.09, 2.30), PFBS (OR=1.37, 95%CI: 1.04, 1.80), PFHxS (OR=1.34, 95%CI: 1.05, 1.71), PFHpS (OR=1.53, 95%CI: 1.10, 2.14), and 6:2 Cl-PFESA (OR=1.34, 95%CI: 1.06, 1.70) were positively correlated with low menstrual blood volume, while PFOA (OR=0.40, 95%CI: 0.23, 0.71), PFHpS (OR=0.45, 95%CI: 0.29, 0.71), and HFPO-DA (OR=0.68, 95%CI: 0.48, 0.97) were negatively correlated with high menstrual blood volume. The mixed exposure model showed that PFAS mixtures were positively correlated with the average number of menstrual cycle days (b=1.60, 95%CI: 0.49, 2.71), irregular menstrual cycles (OR=1.77, 95%CI: 1.19, 2.63), and low menstrual blood volume (OR=1.59, 95%CI: 1.08, 2.35), but negatively correlated with high menstrual blood volume (OR=0.40, 95%CI: 0.22, 0.73). Conclusion Women undergoing ART in Shanghai are widely exposed to PFAS prior to conception. Exposure to PFAS before pregnancy may be related to menstrual characteristics among women seeking ART before undergoing fertility treatments, but additional data from larger populations are required to validate the findings of this study.

ObjectiveTo analyze the prevalence and influencing factors of overweight and obesity among primary school students in a community of Fengxian District, Shanghai, and to provide references for formulating prevention and control strategies against overweight and obesity. MethodsData on height and weight of all primary school students in a community in Fengxian District, Shanghai, in 2023 were obtained by physical examination, and 1 759 primary school students were included according to the entry criteria. Overweight and obesity were determined using body mass index (BMI). Additionally, a questionnaire survey was performed to 1 045 students to collect their demographic characteristics, dietary behaviors, dietary habits, sleep and physical activity information. Chi-square test and logistic regression analysis were used to analyze the influencing factors of overweight and obesity. ResultsIn 2023, among the 1 759 primary school students in the community in Fengxian District, 923 (52.47%) were male and 836 (47.53%) were female, with an overweight/obesity detection rate of 28.08%. The detection rate of overweight and obesity was 33.37% in males and 22.25% in females, which was significantly higher in males than that in females (χ²=26.845, P<0.001). Students aged 10‒12 years had a higher overweight/obesity detection rate (32.55%) than those aged 6‒<10 years (26.53%), and the difference was statistically significant (χ²=10.925, P<0.001). Logistic regression analysis revealed that being female, with young age, parental education level of bachelor’s degree and above, a high global dietary recommendation healthy (GDR-healthy) score, preference for vegetables and sweeter home-cooked meals, and a slow eating speed were negatively correlated with overweight/obesity. Whereas, parental overweight and obesity, binge eating, and a faster eating pace than same-age, same-gender peers may be positively correlated with overweight/obesity. ConclusionThe detection rate of overweight and obesity among primary school students in the community in Fengxian District of Shanghai is higher than the national level. Gender, age, parental BMI, parental education level, dietary behaviors and habits are the main influencing factors of overweight/obesity among primary school students.

OBJECTIVE To investigate the ameliorative effect of ursolic acid on skin inflammation in rats with allergic contact dermatitis （ACD）， and explore its mechanism of action based on the Notch1/hairy and enhancer of split 1 （Hes1） signaling pathway. METHODS The ACD model was established by skin application of 2， 4-dinitrochlorobenzene. Forty successfully modeled rats were randomly divided into model control group （MC group）， ursolic acid low-dose group （UA-L group， 50 mg/kg）， ursolic acid high-dose group （UA-H group， 100 mg/kg）， and ursolic acid high-dose+Notch1 activator group （UA-H+Jagged1 group， 100 mg/kg ursolic acid+50 ng/kg Jagged1）， with 10 rats in each group. Another 10 rats with only hair shedding were selected as the normal control group. Rats in the administration groups were given the corresponding dose of ursolic acid intragastrically or/and Jagged1 by intraperitoneal injection once a day for 14 consecutive days. Twenty-four hours after the last treatment， the skin inflammation status and dermatitis scores of rats in each group were detected. The levels of interleukin-6 （IL-6）， IL-17 and IL-10 in serum and skin tissue were detected by enzyme-linked immunosorbent assay. Hematoxylin-eosin staining was used to detect the pathological morphology of the skin tissue. Immunohistochemical staining and immunoblotting assay were used to detect the protein expressions of Notch1 and Hes1 in skin tissues. RESULTS Compared with the MC group， both the UA-L group and UA-H group exhibited significantly lower dermatitis scores， along with varying degrees of reduction in histopathological skin damage such as inflammatory cell infiltration. Additionally， the levels of IL-6 and IL-17 in serum and skin tissues were markedly decreased， while the levels of IL-10 were significantly increased in both groups； protein expressions of Notch1 and Hes1 were decreased significantly （P＜0.05）， and the improvements in the aforementioned indicators were more significant in the UA-H group （P＜0.05）. Jagged1 could significantly weaken the improvement effects of UA-H on the above indicators （P＜0.05）. CONCLUSIONS Ursolic acid may attenuate the expression of pro-inflammatory cytokines and enhance the expression of anti-inflammatory factors by blocking Notch1/Hes1 signaling pathway， thereby improving dermatitis symptoms in ACD rats.

Gliomas, especially high-grade gliomas such as glioblastoma multiforme (GBM), are primary malignant tumors of the central nervous system, characterized by high proliferative capacity, invasiveness, and therapeutic resistance. The development of GBM relies heavily on continuous metabolic reprogramming to adapt to the unique intracranial microenvironment, with nicotinamide adenine dinucleotide (NAD⁺) metabolic remodeling playing a pivotal role. Dysregulation of NAD⁺ and its associated metabolic pathways sustains increased intracellular NAD⁺ levels, which drive the malignant proliferation and invasive potential of GBM, correlating with worsened patient prognosis. This review systematically summarizes the current research landscape of NAD⁺ metabolic remodeling in GBM, elucidates the mechanisms by which NAD⁺ contributes to GBM pathogenesis and progression, and explores the clinical potential of NAD⁺-targeted diagnostic and therapeutic strategies to provide novel insights and directions for the clinical management of GBM.

Purpose To explore the clinical and pathological features,differential diagnosis,treatment methods and prognosis of urachal adenocarcinoma.Methods Nineteen cases of urachal adenocarcinoma were collected and an-alyzed by combining clinical symptoms,auxiliary examinations,histology,immunohistochemical,and genetic testing and 11 cases of bladder adenocarcinomas.Results Among the 19 patients(15 males,4 females;age range:33-75 years,mean:55 years),tumors were located at the dome or anterior wall of the bladder.Histological subtypes includ-ed mucinous adenocarcinoma(6 cases),adenocarcinoma not otherwise specified(4 cases),enteric-type adenocarci-noma(6 cases),adenocarcinoma with focal mucinous differentiation(1 case),adenocarcinoma with signet-ring cell carcinoma(1 case),and metastatic urachal adenocarcinoma(1 case).Immunophenotypic analysis revealed membra-nous positivity for β-catenin,diffuse positivity for CK34βE 12,MUC-2,and CK20,focal CK7 positivity in some cases,and rare GATA-3 positivity.Mutations in p53 were observed,while KRAS,NRAS,BRAF,and PIK3CA mutations were absent.In colorectal adenocarcinomas,CK34βE12 positivity was 40％,nuclear β-catenin positivity was 48％,and MUC-2 expression was approximately 50％.In bladder adenocarcinomas,GATA-3 and MUC-2 positivity rates were 45％and 63.6％,respectively.Conclusion Distinguishing urachal adenocarcinoma from colorectal and primary bladder adenocarcinomas remains challenging.Urachal adenocarcinoma should be suspected in patients with anterior bladder wall or dome lesions,gross hematuria,or mucinuria.No definitive diagnostic markers currently exist for ura-chal adenocarcinoma.Immunophenotypic features such as membranous β-catenin,MUC-2,and CK7 positivity may fa-vor urachal adenocarcinoma over colorectal adenocarcinoma.Additional markers(e.g.,GATA-3,CK20,CK34βE12)aid in differential diagnosis,though individual markers lack specificity.Comprehensive evaluation integrating clinical presentation,imaging,and clinicopathological features is essential for accurate diagnosis.

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.