1.Effect of Astragali Radix on Gut Microbiota and GLP-1 in Newly Diagnosed Type 2 Diabetes Patients with Qi Deficiency Type
Keke HOU ; Lin CHEN ; Zhidan ZHANG ; Yunyi YANG ; Fangli ZHANG ; Yuanying XU ; Hongping YIN ; Lan DING ; Tao LEI ; Wenjun SHA
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(6):161-170
ObjectiveTo investigate the therapeutic effect of Astragali Radix-mediated changes in gut microbiota on treating type 2 diabetes (T2DM). MethodsA 12-week randomized, placebo-controlled clinical trial enrolled eighty patients with newly diagnosed type 2 diabetes and poor glycemic control in the Qi deficiency type. All patients received insulin therapy. The observation group (40 cases) was administered with Astragali Radix Granules, while the control group (40 cases) received a placebo. Both treamtents were taken orally twice daily. Changes in gut microbiota were assessed by 16s rDNA sequencing. Serum glucagon-like peptide-1 (GLP-1) levels were measured using enzyme-linked immunosorbent assay (ELISA). Glucose metabolism indicators including fasting blood glucose (FPG), 2-hour postprandial blood glucose (2 h PG),glycated albumin(GA), and glycated hemoglobin (HbA1c) were evaluated. Pancreatic function was evaluated using fasting C-peptide (FCP), 2-hour postprandial C-peptide (2 h CP), and C-peptide area under the curve (AUCcp). Traditional Chinese medicine (TCM) syndrome scores, clinical efficacy, and safety indicators were also observed. ResultsIn terms of glucose metabolism indicators, compared with the baseline, both groups exhibited significantly lower FPG, 2 h PG, GA and HbA1C (P<0.01),while FCP, 2 h CP and AUCcp were significantly higher (P<0.01). Compared with the control group after the treatment, the observation group showed significantly lower FPG, 2 h PG, GA and HbA1C(P<0.05, P<0.01),and significantly higher FCP, 2 h CP and AUCcp (P<0.05, P<0.01), indicating that Astragali Radix can improve glucose metabolism. In terms of the diversity of gut microbiota, no significant differences were detected in the Chao1, Shannon and Simpson indexes of the two groups compared with their respective baselines. However, compared with the post-treatment control group, the observation group demonstrated significant increases in the Chao1, Shannon and Simpson indexes (P<0.05, P<0.01). The β-diversity analysis showed significant separation in gut microbiota composition before and after treatment in both groups, indicating that Astragali Radix can significantly alter the structure and improve the diversity of gut microbiota. At the phylum level, compared with the baseline, both groups showed a significant increase in the relative abundance of Bacteroidota(P<0.01). The relative abundance of the potentially harmful phylum Proteobacteria was significantly lower in the observation Group after treatment (P<0.01). Compared with the post-treatment control group, the observation group had a significantly higher relative abundance of Bacteroidota(P<0.01). No significant difference was found in Firmicutes/Bacteroidota (F/B) ratio between the two groups after treatment, and other phyla showed no significant differences. At the genus level, compared with the baseline, the observation group exhibited a significant increase in Bacteroides (P<0.01) and a significant decrease in Escherichia-Shigella (P<0.01), whereas no significant difference was seen in the control group . Compared with the control group after treatment, the observation group after treatment had a significantly higher relative abundance of Bacteroides (P<0.01). No significant differences were seen in other genera. Linear discriminant analysis (LDA) identified potential characteristics taxa: in the observation group, Bacteroidota at the phylum level and Bacteroides and Dubosiella at the genus level, in the control group, Proteobacteria at the phylum level as well as Barnesiella and Staphylococcus at the genus level. Correlation analysis based on a heatmap revealed that GLP-1 levels were positively correlated with Firmicutes, F/B ratio and Fusobacterium, and negatively correlated with Bacteroidota, Proteobacteria, Bacteroides and Escherichia-Shigella. In terms of clinical efficacy, compared with the control group, the total effective rate of the observation group was significantly higher (P<0.05). Compared with the baseline, the scores for shortness of breath, fatigue, weakness, spontaneous sweating and reluctance to speak significantly decreased in both groups (P<0.01). Compared with the control group after treatment, the score for weakness was significantly lower in the observation group (P<0.01),indicating that Astragali Radix could improve clinical symptoms and alleviate weakness symptoms. In terms of safety, compared with the baseline, alanine aminotransferase (ALT) levels significantly decreased in both groups (P<0.05,P<0.01),indicating that Astragali Radix did not induce any significant abnormalities in liver and kidney functions. ConclusionAstragali Radix demonstrates the potential to significantly improve the gut microbiota environment in patients of newly diagnosed type 2 diabetes with Qi deficiency. The therapeutic effect may contribute to glycemic control, possibly mediated by an elevation in GLP-1 level. These findings may support its further clinical investigations and potential applications.
2.The study of m6A methylation-related proteins in the prefrontal cortex of PTSD mice
Jiaying LU ; Luodong YANG ; Keke LU ; Wenlong XIN ; Bin LI ; Qulong LI ; Guiqing ZHANG
Acta Universitatis Medicinalis Anhui 2026;61(3):495-500
ObjectiveTo investigate the expression of prefrontal cortical neurons, methyltransferase-like 3 (METTL3), fat mass and obesity-associated gene (FTO), and AlkB homolog 5 (ALKBH5) proteins in a mouse model of post-traumatic stress disorder (PTSD). MethodsA PTSD mouse model was established using a single prolonged stress and foot shock stimulation (SPSS) method. The despair, anxiety, and learning and memory functions of PTSD mice were assessed through the open field test, Y-maze test, and forced swimming test. Neuronal damage was detected via HE and Nissl staining. The expression levels of METTL3, FTO, ALKBH5, and neuronal nuclear protein (NEUN) were assessed by Western blot and immunofluorescence staining. ResultsCompared to control group, PTSD mice subjected to SPSS exhibited signs of despair, anxiety, and impaired learning and memory. HE and Nissl staining results showed neuronal damage in the prefrontal cortex of PTSD mice. Western blot and immunofluorescence staining results showed that the expression of the m6A-related proteins METTL3 and FTO decreased, while the expression of ALKBH5 increased in the prefrontal cortex. Additionally, NEUN protein levels showed a declining trend. ConclusionThe pathogenesis of PTSD may be associated with neuronal damage in the prefrontal cortex and alterations in m6A methylation proteins.
3.Analysis and prediction of disease burden of idiopathic epilepsy in China
Xiaojun WANG ; Chenwei LI ; Jianglin RAN ; Zhiheng FENG ; Keke YANG ; Huiyuan PENG
Chinese Journal of Neuromedicine 2025;24(7):689-698
Objective:To describe the temporal trend of disease burden of idiopathic epilepsy in China from 1990 to 2021 and predict the incidence of idiopathic epilepsy in China from 2022 to 2035 to provide references for the formulation of relevant health policies and measures.Methods:Based on data from the Global Burden of Disease Study 2021 (GBD 2021) database regarding idiopathic epilepsy in China, changes in disease burden from 1990 to 2021 were acquired. Disease burden was quantified using age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), age-standardized mortality rate (ASMR), age-standardized disability-adjusted life years (DALYs) rate (ASDR) and their 95% uncertain interval (UI). Temporal trend analysis was performed using a linear regression model to estimate the estimated annual percent change (EAPC) and annual percentage change (APC) in incidence of idiopathic epilepsy and their 95% CI. Additionally, incidence and number of patients with idiopathic epilepsy in China from 2022 to 2035 were predicted using Bayesian age-period-cohort model. Results:The ASIR of idiopathic epilepsy increased from 22.35 per 100,000 population in 1990 (95% UI: 15.04-30.92 per 100,000 population) to 28.19 per 100,000 population in 2021 (95% UI: 19.03-37.89 per 100,000 population), with an EAPC of 0.12% (95% CI: -0.10%-0.34%); ASPR of idiopathic epilepsy increased from 189.27 per 100,000 population in 1990 (95% UI: 132.48-252.95 per 100,000 population) to 214.71 per 100,000 population in 2021 (95% UI: 150.10-278.56 per 100,000 population), with an EAPC of -0.32% (95% CI: -0.57%-0.06%); ASMR of idiopathic epilepsy decreased from 1.86 per 100,000 population in 1990 (95% UI: 1.59-2.24 per 100,000 population) to 0.80 per 100,000 population in 2021 (95% UI: 0.67-1.00 per 100,000 population), with an EAPC of -2.96% (95% CI: -3.09%-2.82%); ASDR of idiopathic epilepsy decreased from 178.60 per 100,000 population in 1990 (95% UI: 143.44-220.63 per 100,000 population) to 101.39 per 100,000 population in 2021 (95% UI: 72.51-139.40 per 100,000 population), with an EAPC of -2.38% (95% CI: -2.54%-2.22%). The prediction model showed that by 2035, the prevalence of idiopathic epilepsy in China will be 28.27 per 100,000 (95% CI: 23.19-38.66), with an estimated 394,928 incident cases (95% CI: 324,037-540,128). Conclusions:From 1990 to 2021, the ASIR and ASPR of idiopathic epilepsy in China show an upward trend, while the ASMR and ASDR hace a decline trend. Incidence of idiopathic epilepsy in China is expected to remain stable over the next decade.
4.Quality control protocol for adult overweight and obesity screening in health management (examination) institutions (2025 edition)
Jianling FAN ; Tiejun WANG ; Pengfei YANG ; Keke DING ; Xiaoning HAO ; Sunfang JIANG ; Ankang LÜ ; Jianping LU ; Sheng RONG ; Weibin SHI ; Shengwei SUN ; Yan TAN ; Qilei TU ; Zhiping WANG ; Bing WANG ; Jianyun WANG ; Weijian WANG ; Yan WANG ; Qun XU ; Chenli ZHANG ; Fan ZHANG ; Ping ZHANG ; Yansong ZHENG ; Jieru ZHOU ; Dan CHEN ; Jiaoyang ZHENG
Chinese Journal of Clinical Medicine 2025;32(6):1097-1111
Obesity, as a chronic recurrent disease, has become a major public health challenge in China. To implement the requirements of the Healthy China Initiative (2019—2030), under domestic guidelines or consensus statements on overweight and obesity, and in alignment with the latest scientific advances globally, the Quality control protocol for adult overweight and obesity screening in health management (examination) institutions (2025 edition) was developed. This protocol was drafted by the Health Management Center of Shanghai Changzheng Hospital and formulated through multiple rounds of deliberation by experts in China’s health examination quality control field. The protocol establishes unified standards for screening facilities, personnel qualifications, and measurement or testing procedures. It defines specific screening items, outlines a standardized screening pathway, and sets requirements for the final medical review, ensuring the scientific validity, effectiveness, and safety of the screening process. The implementation of this protocol will enhance the consistency of weight management practices for adults across health examination institutions and strengthen the quality control of overweight and obesity screening programs.
5.Research advances in machine learning for prognosis and risk of adverse event prediction after mechanical thrombectomy in acute anterior circulation large vessel occlusion
Chenwei LI ; Keke YANG ; Xiaojun WANG ; Weihua GUO ; Zhiheng FENG ; Huiyuan PENG
Chinese Journal of Cerebrovascular Diseases 2025;22(3):210-216,后插1
Acute large vessel occlusion stroke(ALVOS)of anterior circulation is associated with severe clinical manifestations and high rates of disability and mortality.Mechanical thrombectomy has emerged as the primary therapeutic intervention.However,post-procedural outcomes remain highly variable,and patients continue to face elevated risks of poor prognosis.Machine learning,a transformative tool in medical research,enables comprehensive analysis of multimodal data to identify specific biomarkers and improve the accuracy of predictions for clinical outcomes and adverse events.This review summarized the latest developments in machine learning applications aim at predicting post-thrombectomy prognosis and risk of adverse event,including futile recanalization,hemorrhagic transformation,and malignant cerebral edema in patients with anterior circulation ALVOS in order to provide a basis for developing personalized treatment plan and improve their clinical prognosis.
6.Research advances in machine learning for prognosis and risk of adverse event prediction after mechanical thrombectomy in acute anterior circulation large vessel occlusion
Chenwei LI ; Keke YANG ; Xiaojun WANG ; Weihua GUO ; Zhiheng FENG ; Huiyuan PENG
Chinese Journal of Cerebrovascular Diseases 2025;22(3):210-216,后插1
Acute large vessel occlusion stroke(ALVOS)of anterior circulation is associated with severe clinical manifestations and high rates of disability and mortality.Mechanical thrombectomy has emerged as the primary therapeutic intervention.However,post-procedural outcomes remain highly variable,and patients continue to face elevated risks of poor prognosis.Machine learning,a transformative tool in medical research,enables comprehensive analysis of multimodal data to identify specific biomarkers and improve the accuracy of predictions for clinical outcomes and adverse events.This review summarized the latest developments in machine learning applications aim at predicting post-thrombectomy prognosis and risk of adverse event,including futile recanalization,hemorrhagic transformation,and malignant cerebral edema in patients with anterior circulation ALVOS in order to provide a basis for developing personalized treatment plan and improve their clinical prognosis.
7.Analysis and prediction of disease burden of idiopathic epilepsy in China
Xiaojun WANG ; Chenwei LI ; Jianglin RAN ; Zhiheng FENG ; Keke YANG ; Huiyuan PENG
Chinese Journal of Neuromedicine 2025;24(7):689-698
Objective:To describe the temporal trend of disease burden of idiopathic epilepsy in China from 1990 to 2021 and predict the incidence of idiopathic epilepsy in China from 2022 to 2035 to provide references for the formulation of relevant health policies and measures.Methods:Based on data from the Global Burden of Disease Study 2021 (GBD 2021) database regarding idiopathic epilepsy in China, changes in disease burden from 1990 to 2021 were acquired. Disease burden was quantified using age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), age-standardized mortality rate (ASMR), age-standardized disability-adjusted life years (DALYs) rate (ASDR) and their 95% uncertain interval (UI). Temporal trend analysis was performed using a linear regression model to estimate the estimated annual percent change (EAPC) and annual percentage change (APC) in incidence of idiopathic epilepsy and their 95% CI. Additionally, incidence and number of patients with idiopathic epilepsy in China from 2022 to 2035 were predicted using Bayesian age-period-cohort model. Results:The ASIR of idiopathic epilepsy increased from 22.35 per 100,000 population in 1990 (95% UI: 15.04-30.92 per 100,000 population) to 28.19 per 100,000 population in 2021 (95% UI: 19.03-37.89 per 100,000 population), with an EAPC of 0.12% (95% CI: -0.10%-0.34%); ASPR of idiopathic epilepsy increased from 189.27 per 100,000 population in 1990 (95% UI: 132.48-252.95 per 100,000 population) to 214.71 per 100,000 population in 2021 (95% UI: 150.10-278.56 per 100,000 population), with an EAPC of -0.32% (95% CI: -0.57%-0.06%); ASMR of idiopathic epilepsy decreased from 1.86 per 100,000 population in 1990 (95% UI: 1.59-2.24 per 100,000 population) to 0.80 per 100,000 population in 2021 (95% UI: 0.67-1.00 per 100,000 population), with an EAPC of -2.96% (95% CI: -3.09%-2.82%); ASDR of idiopathic epilepsy decreased from 178.60 per 100,000 population in 1990 (95% UI: 143.44-220.63 per 100,000 population) to 101.39 per 100,000 population in 2021 (95% UI: 72.51-139.40 per 100,000 population), with an EAPC of -2.38% (95% CI: -2.54%-2.22%). The prediction model showed that by 2035, the prevalence of idiopathic epilepsy in China will be 28.27 per 100,000 (95% CI: 23.19-38.66), with an estimated 394,928 incident cases (95% CI: 324,037-540,128). Conclusions:From 1990 to 2021, the ASIR and ASPR of idiopathic epilepsy in China show an upward trend, while the ASMR and ASDR hace a decline trend. Incidence of idiopathic epilepsy in China is expected to remain stable over the next decade.
8.Study on the latent profile characteristics and influencing factors of capability-opportunity-motivation-behavior in stroke patients
Lina GUO ; Yuying XIE ; Mengyu ZHANG ; Xinxin ZHOU ; Peng ZHAO ; Miao WEI ; Han CHENG ; Qingyang LI ; Caixia YANG ; Keke MA ; Yanjin LIU ; Yuanli GUO
Chinese Journal of Modern Nursing 2024;30(25):3374-3381
Objective:To explore the latent profile types of capability-opportunity-motivation-behavior in stroke patients and analyze the influencing factors of different latent profiles.Methods:From January to October 2023, totally 596 stroke patients from the Neurology Department of five ClassⅢ Grade A hospitals in Henan Province were selected by stratified random sampling. The patients were surveyed using a general information questionnaire, the Stroke Prevention Knowledge Questionnaire (SPKQ), the Social Support Rating Scale (SSRS), the WHO's Quality of Life Questionnaire- Brief Version (WHOQOL-BREF), the Short Form Health Belief Model Scale (SF-HBMS), and the Health Promoting Lifestyle ProfileⅡ (HPLPⅡ). Latent profile analysis was used to classify the capability-opportunity-motivation-behavior characteristics of stroke patients, and multiple logistic regression was conducted to explore the influencing factors of different latent profiles.Results:Three latent profiles of capability-opportunity-motivation-behavior in stroke patients were identified, including low capability-opportunity-motivation-behavior with high health beliefs (32.4%, 193/596), moderate capability-opportunity-motivation-behavior with insufficient health beliefs (47.5%, 283/596), and high capability-opportunity-motivation-behavior with lack of social support (20.1%, 120/596). Multiple logistic regression analysis showed that educational level, smoking history, family history, body mass index, and Charlson Comorbidity Index score were influencing factors of different latent profiles ( P<0.05) . Conclusions:Stroke patients exhibit distinct classifications of capability-opportunity-motivation-behavior. Targeted interventions should be conducted based on the characteristics of each category to improve health behavior management outcomes in patients.
9.Analysis of the predictive value of amplitude integrated electroencephalogrphy and brainstem auditory evoked potentials for cognitive and affective disorder in patients with cerebral small vessel disease
Rui WANG ; Keke HAN ; Yonggang HAO ; Lihui YANG ; Wanli DONG
Chinese Journal of Cerebrovascular Diseases 2024;21(12):813-822
Objective Exploring the predictive value of amplitude integrated electroencephalography(aEEG)and brainstem auditory evoked potentials(BAEP)in cognitive and affective disorders related to cerebral small vessel disease(CSVD).Methods Retrospectively,100 patients with CSVD who visited the Department of Neurology at the Fourth Affiliated Hospital of Soochow University from January 2021 to February 2024 were included in the CSVD group.From January 2021 to February 2024,100 healthy people who underwent physical examination in the Physical Examination Center of the Fourth Affiliated Hospital of Soochow University and matched with the CSVD group for age and sex were prospectively included as the control group.Basic and clinical data were collected and compared between the CSVD group and the control group,including age,sex,years of education,hypertension,diabetes,smoking,drinking,total cholesterol,triglycerides,low-density lipoprotein cholesterol(LDL-C),C-reactive protein(CRP),galactin-3(Gal-3),cystatin C,homocysteine(Hcy),blood Tau protein,and glial fibrillary acidic protein(GFAP).Cognitive function was assessed using the mini-mental state examination(MMSE)and the Montreal cognitive assessment(MoCA)scale,with a MMSE score<24 and a MoCA score<25 indicating cognitive impairment.affective disorders were assessed using the Hamilton anxiety scale(HAMA)and the Hamilton depression scale(HAMD),with a HAMA score ≥ 14 or a HAMD score ≥20 indicating the presence of affective disorders.The scores of the above four scales were compared between the CSVD group and the control group.aEEG and BAEP data were collected and compared between the CSVD group and the control group.aEEG results were evaluated based on a composite score of background activity stability,sleep-wake cycle,lower boundary amplitude,and narrowband width,with a score of 0-3 indicating aEEG abnormalities.In the BAEP waveform,the Ⅰ,Ⅲ,and Ⅴ waves and the inter-wave intervals of Ⅰ-Ⅲ,Ⅲ-Ⅴ and Ⅰ-Ⅴ were observed and recorded,along with their peak latencies and inter-peak latencies.If the latency of each wave is prolonged>mean+3 standard deviations and/or the interwave period is prolonged>mean+3 standard deviations,it was considered a BAEP abnormality.CSVD patients were divided into cognitive impairment and non-cognitive impairment based on MMSE scale score and MoCA scale score,and all CSVD patients were divided into affective disorder and non-affective disorder based on HAMA score and HAMD score.The independent variables with statistically significant differences and no collinearity in the univariate analysis of cognitive and affective disorders in CSVD patients were included in the multivariate Logistic regression analysis,and the statistically significant factors were used to form the multivariate model.The area under the receiver operating characteristic(ROC)curve was used to analyze the predictive value of the multi-factor model for CSVD-related cognitive and affective disorders.Results(1)The proportion of hypertension patients,the levels of CRP,Gal-3,cystatin C,Hcy,Tau protein,GFAP,HAMA and HAMD scores in the CSVD group were higher than those in the control group(all P<0.05),and the MMSE and MoCA scale were lower than those in the control group(both P<0.05).The scores of continuity,sleep-wake cycle,lower boundary amplitude and narrow band width of aEEG in the CSVD group were lower than those in the control group(all P<0.05).The peak latency and interpeak latency of BAEP in the CSVD group were higher than those in the control group(all P<0.05).(2)There were 52 patients with cognitive impairment and 48 patients with non-cognitive impairment in CSVD patients.There were 36 patients with affective disorder and 64 patients with non-affective disorder.There were 17patients with both cognitive and affective disorders.The age,Tau protein,GFAP,the proportion of patients with abnormal aEEG and the proportion of patients with abnormal BAEP in patients with cognitive impairment were higher than those in patients without cognitive impairment(all P<0.05).The age of patients with affective disorder,the proportion of patients with abnormal aEEG and the proportion of patients with abnormal BAEP were higher than those of patients without affective disorder(all P<0.05).(3)Multivariate Logistic regression analysis showed that the risk of cognitive impairment in patients with abnormal aEEG CSVD was 4.364 times higher than that in patients with normal aEEG CSVD(OR,4.364,95%CI 1.554-12.252,P=0.005).The risk of cognitive impairment in patients with abnormal BAEP CSVD was 3.218 times higher than that in patients with normal BAEP CSVD(OR,3.218,95%CI 1.218-8.503,P=0.018).The ROC curve was used to analyze the predictive value of the multi-factor model jointly constructed by aEEG abnormalities and BAEP abnormalities for CSVD cognitive impairment.The results showed that the area under the ROC curve was 0.732,the sensitivity was 76.38%,and the specificity was 82.59%.(4)Multivariate Logistic regression analysis showed that the risk of affective disorder in patients with abnormal aEEG CSVD was 3.203 times higher than that in patients with normal aEEG CSVD(OR,3.203,95%CI 1.288-7.966,P=0.012).The risk of affective disorder in patients with abnormal BAEP CSVD was 2.553 times higher than that in patients with normal BAEP CSVD(OR,2.553,95%CI 1.011-6.446,P=0.047).The ROC curve was used to analyze the predictive value of the multi-factor model jointly constructed by aEEG abnormalities and BAEP abnormalities for CSVD affective disorders.The results showed that the area under the ROC curve was 0.700,the sensitivity was 74.21%,and the specificity was 83.49%.Conclusions The abnormality of aEEG and BAEP are important factors in constructing the prediction model of cognitive and affective disorders in CSVD patients.The multi-factor model constructed by aEEG and BAEP has certain value in predicting CSVD-related cognitive and affective disorders.
10.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.

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