1.Risk factors analysis and prediction model construction of SGLT2 inhibitor-associated euglycemic diabetic ketoacidosis
Wenhui HUANG ; Xiufen CHEN ; Jianming CHEN ; Yana HONG ; Jingjing CAI ; Jinshan CHEN
Journal of Pharmaceutical Practice and Service 2026;44(5):247-252
Objective To explore risk factors of sodium-dependent glucose transporters 2 (SGLT2) inhibitor-associated euglycemic diabetic ketoacidosis (euDKA) and to construct a risk prediction model. Methods A retrospective analysis was performed on the clinical data of type 2 diabetes patients treated with SGLT2 inhibitors in Dongnan Hospital of Xiamen University from January 2020 to December 2023, including age, gender and course of diabetes. The risk factors of SGLT2 inhibitor-associated euDKA were analyzed by univariate analysis and multivariate Logistic regression, and a prediction model was established. According to the receiver's operating characteristic (ROC) curve, the area under the curve (AUC) and the optimal critical value of the prediction model were determined. The prediction model was subjected to both internal and external validation. Results A total of 119 patients with type 2 diabetes treated with SGLT2 inhibitors were included in this study. Among them, there were 98 cases without euDKA (non-euDKA group)and 21 cases with euDKA (euDKA group). Multivariate Logistic regression analysis showed the DKA history (OR=114.153), appetite or diet decreased three days before admission (OR=21.774), elevated neutrophil count (OR=2.056) and pre-hospital adjustment of hypoglycemic agents (OR=45.745) were independent factors to increase risks of euDKA associated with SGLT2 inhibitors (P<0.05). Surgical history before admission was an independent factor to reduce this risk (OR=0.007, P<0.05). By establishing the calculation formula of the prediction model = neutrophil count+6.571 (DKA history)−6.874 (surgical history before admission)+4.273 (appetite or diet decreased three days before admission)+5.302 (pre-hospital adjustment of hypoglycemic drugs), the ROC curve was drawn. The AUC of the ROC of the prediction model was 0.982 (95%CI: 0.961-1.000, P<0.001), with accuracy of 94.96%, sensitivity of 0.905, specificity of 0.959 and a critical value of 7.405. The AUC of ROC curve after the model’s ten-fold cross validation was 0.930. And the accuracy of the external validation of the prediction model was 85.29%. Conclusion The DKA history, appetite or diet decreased three days before admission, elevated neutrophil count and pre-hospital adjustment of hypoglycemic agents increased the risk of SGLT2 inhibitor-associated euDKA, while the surgical history before admission reduced this risk. The risk prediction model constructed on this basis could better predict the risk of SGLT2 inhibitor-associated euDKA.
2.Unveiling the molecular and cellular links between obstructive sleep apnea-hypopnea syndrome and vascular aging.
Wei LIU ; Le ZHANG ; Wenhui LIAO ; Huiguo LIU ; Wukaiyang LIANG ; Jinhua YAN ; Yi HUANG ; Tao JIANG ; Qian WANG ; Cuntai ZHANG
Chinese Medical Journal 2025;138(2):155-171
Vascular aging (VA) is a common etiology of various chronic diseases and represents a major public health concern. Intermittent hypoxia (IH) associated with obstructive sleep apnea-hypopnea syndrome (OSAHS) is a primary pathological and physiological driver of OSAHS-induced systemic complications. A substantial proportion of OSAHS patients, estimated to be between 40% and 80%, have comorbidities such as hypertension, heart failure, coronary artery disease, pulmonary hypertension, atrial fibrillation, aneurysm, and stroke, all of which are closely associated with VA. This review examines the molecular and cellular features common to both OSAHS and VA, highlighting decreased melatonin secretion, impaired autophagy, increased apoptosis, increased inflammation and pyroptosis, increased oxidative stress, accelerated telomere shortening, accelerated stem cell depletion, metabolic disorders, imbalanced protein homeostasis, epigenetic alterations, and dysregulated neurohormonal signaling. The accumulation and combination of these features may underlie the pathophysiological link between OSAHS and VA, but the exact mechanisms by which OSAHS affects VA may require further investigation. Taken together, these findings suggest that OSAHS may serve as a novel risk factor for VA and related vascular disorders, and that targeting these features may offer therapeutic potential to mitigate the vascular risks associated with OSAHS.
Humans
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Sleep Apnea, Obstructive/pathology*
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Aging/physiology*
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Oxidative Stress/physiology*
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Animals
3.Autophagy in Oligodendrocyte Lineage Cells Controls Oligodendrocyte Numbers and Myelin Integrity in an Age-dependent Manner.
Hong CHEN ; Gang YANG ; De-En XU ; Yu-Tong DU ; Chao ZHU ; Hua HU ; Li LUO ; Lei FENG ; Wenhui HUANG ; Yan-Yun SUN ; Quan-Hong MA
Neuroscience Bulletin 2025;41(3):374-390
Oligodendrocyte lineage cells, including oligodendrocyte precursor cells (OPCs) and oligodendrocytes (OLs), are essential in establishing and maintaining brain circuits. Autophagy is a conserved process that keeps the quality of organelles and proteostasis. The role of autophagy in oligodendrocyte lineage cells remains unclear. The present study shows that autophagy is required to maintain the number of OPCs/OLs and myelin integrity during brain aging. Inactivation of autophagy in oligodendrocyte lineage cells increases the number of OPCs/OLs in the developing brain while exaggerating the loss of OPCs/OLs with brain aging. Inactivation of autophagy in oligodendrocyte lineage cells impairs the turnover of myelin basic protein (MBP). It causes MBP to accumulate in the cytoplasm as multimeric aggregates and fails to be incorporated into integral myelin, which is associated with attenuated endocytic recycling. Inactivation of autophagy in oligodendrocyte lineage cells impairs myelin integrity and causes demyelination. Thus, this study shows autophagy is required to maintain myelin quality during aging by controlling the turnover of myelin components.
Animals
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Autophagy/physiology*
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Oligodendroglia/metabolism*
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Myelin Sheath/physiology*
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Aging/pathology*
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Myelin Basic Protein/metabolism*
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Cell Lineage/physiology*
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Mice
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Oligodendrocyte Precursor Cells
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Mice, Inbred C57BL
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Brain/cytology*
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Cells, Cultured
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Cell Count
4.Correction to: Autophagy in Oligodendrocyte Lineage Cells Controls Oligodendrocyte Numbers and Myelin Integrity in an Age-dependent Manner.
Hong CHEN ; Gang YANG ; De-En XU ; Yu-Tong DU ; Chao ZHU ; Hua HU ; Li LUO ; Lei FENG ; Wenhui HUANG ; Yan-Yun SUN ; Quan-Hong MA
Neuroscience Bulletin 2025;41(3):547-548
5.Effect of Erchen Decoction (二陈汤) on Serum Leptin and Expression of LepR,POMC,and NPY in Hypothalamus of Metabolic Syndrome Model Mice with Phlegm Syndrome
Menghan YANG ; Yuanyuan LI ; Xiujuan ZHENG ; Wenhui XIONG ; Xirui HUANG ; Bizhen GAO
Journal of Traditional Chinese Medicine 2025;66(9):948-954
ObjectiveTo explore the potential mechanism of Erchen Decoction (二陈汤, ECD) in improving metabolic syndrome (MS) with phlegm syndrome. MethodsForty mice were randomly divided into a blank group of 10 mice and a modeling group of 30 mice. The MS model with phlegm syndrome was induced in the modeling group by high-fat diet. Thirty successfully modeled mice were randomly divided into a model group, a ECD group, and a metformin group, with 10 mice in each group. The ECD group was given 0.4 g/(kg·d) of ECD, while the metformin group was intervened with 11.1 g/(kg·d) of metformin solution, and the blank group and the model group were given 0.02 ml/(g·d) of sterilized drinking water, all by gavage, once daily for 4 weeks. Body weight, abdominal circumfe-rence, body length, Lee's index and food intake were recorded. Blood glucose and blood lipid levels including fasting blood glucose, triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured. ELISA was used to detect serum leptin levels, while HE staining was used to observe liver pathological changes. Western Blot and q-PCR were used to detect protein and mRNA expression of hypothalamic leptin receptor (LepR), pro melanocortin (POMC), and neuropeptide Y (NPY) in the hypothalamus. Immunofluorescence was used to detect fluorescence expression of POMC and NPY in the hypothalamic arcuate nucleus region. ResultsPathological results showed that the mice in the model group had numerous fat vacuoles in hepatocytes and significant liver fat deposition, while the ECD and metformin groups showed reduced fat vacuoles and less liver fat deposition. Compared to those in the blank group, the mice in the model group mice showed liver fat deposition, increased body weight, abdominal circumference, Lee's index and food intake; fasting blood glucose, TG, TC, LDL-C, and serum leptin levels were elevated, while HDL-C was decreased; the expression of LepR, POMC protein levels and their mRNA expression decreased, while the protein level and mRNA expression of NPY increased; the fluorescence expression of POMC in the arcuate nucleus was reduced, while NPY fluorescence expression increased (P<0.05 or P<0.01). Compared to the model group, the ECD group and metformin group showed significant improvements in the above indicators (P<0.05 or P<0.01). Compared to the ECD group, the metformin group showed a reduction in body weight and NPY fluorescence expression, and an increase in HDL-C levels (P<0.05 or P<0.01). ConclusionECD can downregulate serum leptin levels and improve glucose and lipid metabolism in the MS of phlegm syndrome. Its mechanism of action may be to reduce liver fat deposition and thereafter affect the expression of neuropeptides related to feeding activity in the hypothalamus.
6.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
7.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; 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 ; 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 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 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
8.Analysis of salary satisfaction and influencing factors of medical staff in public hospitals in Guangxi
Yanlong WU ; Wenhui ZHUANG ; Junjie HUANG ; Pinghua ZHU
Chinese Journal of Hospital Administration 2025;41(2):119-126
Objective:To analyze the salary satisfaction and influencing factors of medical staff in public hospitals in Guangxi under the background of salary system reform, and to provide suggestions for deepening the salary system reform of public hospitals in Guangxi.Methods:From July to December 2022, medical staff from 39 public hospitals that have carried out salary system reform were selected through stratified random sampling, and self-made questionnaires were used to survey them, which mainly included salary, salary expectations and salary satisfaction. Descriptive analysis of the questionnaire data was performed, and binary logistic regression was used to analyze the influencing factors of salary satisfaction.Results:A total of 10 299 valid questionnaires were obtained. 6 869 (66.7%) medical staff had a lower average monthly income after tax than those employed in urban non-private units in Guangxi in that year; 8 100 (78.6%) medical staff expected to be paid 30%~50% higher than the current salary level; 4 073 (39.5%) were satisfied with the overall salary satisfaction, of which 2 377 (23.1%) were satisfied with the salary increase after the reform of the salary system in 2017. The results of multivariate analysis showed that education, hospital type, hospital level, professional title, position and job type were the main influencing factors of salary satisfaction of medical staff ( P<0.05), and hospital level interacted with education, hospital type and job type respectively ( P<0.05). Conclusions:The external competitiveness of the salary of medical staff in Guangxi was insufficient, and the salary satisfaction was not high. It is suggested to pay attention to the inter-embeddedness of the reform of the salary system and the reform of the " three-medical linkage" , pay attention to the balanced development of different levels and types of hospitals, scientifically calculate the value coefficient of different positions, and effectively improve the salary level of medical staff.
9.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; 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 ; 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 ; Hong ZHANG ; Chun WANG ; 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(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
10.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; 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 ; 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 WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

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