1.Expert consensus on visualized tele-round and quality control management based on the improvement of clinical practice ability
Wanhong YIN ; Xiaoting WANG ; Ran ZHOU ; Dawei LIU ; Yan KANG ; Yaoqing TANG ; Xiaochun MA ; Jianguo LI ; Zhenjie HU ; Haitao ZHANG ; Wei HE ; Lixia LIU ; Wenjin CHEN ; Ran ZHU ; Jun WU ; Hongmin ZHANG ; Lina ZHANG ; Wenzhao CHAI ; Shihong ZHU ; Wangbin XU ; Rongqing SUN ; Xiangyou YU ; Tianjiao SONG ; Ying ZHU ; Hong REN ; Ai SHANMU ; Qing ZHANG ; Wei FANG ; Xiuling SHANG ; Liwen LYU ; Shuhan CAI ; Xin DING ; Heng ZHANG ; Guang FENG ; Lipeng ZHANG ; Bo HU ; Dong ZHANG ; Weidong WU ; Feng SHEN ; Xiaojun YANG ; Zhenguo ZENG ; Qibing HUANG ; Xueying ZENG ; Tongjuan ZOU ; Milin PENG ; Yulong YAO ; Mingming CHEN ; Hui LIAN ; Jingmei WANG ; Yong LI ; Feng QU ; Gang YE ; Rongli YANG ; Xiukai CHEN ; Suwei LI ; Juxiang WANG ; Yangong CHAO
Chinese Journal of Internal Medicine 2025;64(2):101-109
Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.
2.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.
3.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.
4.The impact of metabolic syndrome combined with high-sensitivity C-reactive protein on the risk of digestive system malignant tumors: a prospective cohort study
Jiaxing LI ; Kuan LIU ; Chao MA ; Wanchao WANG ; Yuan TIAN ; Taixian JIANG ; Zhigang DONG ; Wenqiang WEI ; Shouling WU ; Siqing LIU
Chinese Journal of Digestion 2025;45(2):73-81
Objective:To explore the correlation between metabolic syndrome (MS), serum high-sensitivity C-reactive protein (hs-CRP) levels, their combination and the risk of digestive system malignancies.Methods:A prospective cohort study was conducted in the participants from the Kailuan cohort who took health examination in July 2006. Anthropometric parameters, epidemiological information, and laboratory test results were collected. Incidence and mortality of digestive system malignant tumors were collected through biennial health examinations and questionnaires. The follow-up period ended on December 31, 2021.According to MS status and hs-CRP levels (hs-CRP≤3 or >3 mg/L), the cohort was divided into 4 groups, induding MS -hs-CRP -, MS -hs-CRP +, MS + hs-CRP -, and MS + hs-CRP + group. Chi-squared test, one analysis of variance, and the Kruskal-Wallis H test were used for inter-group comparison among groups. Kaplan-Meier method was used to calculate the cumulative incidence of digestive system malignant tumors, and log-rank test was performed to compare the cumulative incidence among groups. Multivariable Cox proportional hazards regression models were used to evaluate the effects of MS and hs-CRP levels on the overall risk of digestive system malignant tumors, as well as the effects of their combination on the risk of digestive system malignant tumors of different site, and relevant confounding factors were adjusted.A sensitivity analysis was conducted by excluding individuals diagnosed with digestive system malignancies within one year of follow-up, as well as those taking antihypertensive, antidiabetic, or lipid-lowering medications. Results:A total of 92 916 participants were included in this study. Among them, 57 933 cases were in the MS -hs-CRP - group, 10 949 cases in the MS -hs-CRP + group, 18 412 cases in the MS + hs-CRP - group, and 5 622 cases in the MS + hs-CRP + group.The median follow-up period was 15.01 years (14.66 to 15.20 years). By the end of follow-up, these were 1 992 cases of new-onset digestive system malignant tumors. The cumulative incidence rates of digestive system malignant tumors of MS -hs-CRP -, MS -hs-CRP +, MS + hs-CRP -, and MS + hs-CRP + groups were 2.0%(1 164/57 933), 2.3%(249/10 949), 2.4%(440/18 412), and 2.5%(139/5 622), respectively. The difference in the cumulative incidence among the 4 groups was statistically significant ( χ2=14.09, P=0.003).The results of multivariate Cox analysis showed that, after hs-CRP level and other confounding factors were adjusted, the risk of developing digestive system malignant tumors in participants with MS was 21.4% higher than that in those without MS ( HR=1.214 (95% confidence interval (95% CI): 1.086 to 1.340), P<0.001). After MS status and other confounding factors were adjusted, the risk of developing digestive system malignant tumors in participants with high hs-CRP level (>3 mg/L) was 17.2% higher than those with low hs-CRP level (≤3 mg/L) ( HR=1.172 (95% CI: 1.042 to 1.303), P=0.008). After relevant confounding factors were adjusted, the risks of developing digestive system malignant tumors in the MS -hs-CRP +, MS + hs-CRP -, and MS + hs-CRP + groups increased by 17.2%, 21.4%, and 35.9%, respectively, as compared with that of the MS -hs-CRP - group ( HR=1.172 (95% CI: 1.017 to 1.399), P=0.028; HR=1.214 (95% CI: 1.074 to 1.356), P=0.002; HR=1.359 (95% CI: 1.135 to 1.635), P=0.001). Among the 4 groups, the overall risk of developing digestive system malignant tumors of MS + hs-CRP + group was the highest. After relevant confounding factors were adjusted, the risks of colorectal cancer, liver cancer, and pancreatic cancer of the MS + hs-CRP + group increased by 46.2%, 35.7%, and 88.3%, respectively, as compared with those of the MS -hs-CRP - group ( HR=1.462 (95% CI: 1.088 to 1.956), HR=1.357 (95% CI: 1.132 to 2.089), HR=1.883 (95% CI: 1.052 to 3.342)), suggesting that MS combined with high hs-CRP was a significant risk factor for increased incidences of colorectal cancer, liver cancer, and pancreatic cancer ( P=0.012, 0.016 and 0.033). After participants diagnosed with new digestive system malignancies within one year of follow-up and those taking antihypertensive, antidiabetic, or lipid-lowering medications (108 cases, 10 680 cases, 2 344 cases, 906 cases) were excluded, the results of sensitivity analysis indicated the increased risk of digestive system malignant tumors in the MS -hs-CRP +, MS + hs-CRP -, and MS + hs-CRP + groups were 12.1%, 21.4%, 28.7%; 18.2%, 21.4%, 24.8%; 16.4%, 21.4%, 32.2%; 17.3%, 20.4%, 35.8%. Among the 3 groups, the increased risk of developing digestive system malignant tumors of MS + hs-CRP + group was the highest. Conclusion:MS and hs-CRP >3 mg/L are both independent risk factors for developing digestive system malignant tumors, and their combination further increases the risk of developing digestive system malignant tumors.
5.The influence of diabetes mellitus and high-sensitivity C-reactive protein on the risk of diges-tive system malignancy: a prospective cohort study
Kuan LIU ; Jiaxing LI ; Chao MA ; Wanchao WANG ; Yuan TIAN ; Zhigang DONG ; Wenqiang WEI ; Shuohua CHEN ; Shouling WU ; Siqing LIU
Chinese Journal of Digestive Surgery 2025;24(1):93-102
Objective:To investigate the influence of diabetes mellitus (DM) and high-sen-sitivity C-reactive protein (Hs-CRP) on the risk of digestive system malignancy.Methods:The pro-spective cohort study was conducted. The clinical data of 93 928 participants who participated health examination in 9 hospitals at Tangshan, including Kailuan General Hospital Affiliated to North China University of Science and Technology et al, in 2006 were selected. According to the presence or absence of DM and the level of Hs-CRP, all participants were divided into 4 groups, including the DM(-)CRP(-) group defined as absence of DM and Hs-CRP ≤3 mg/L, the DM(-)CRP(+) group defined as absence of DM and Hs-CRP>3 mg/L, the DM(+)CRP(-) group defined as presence of DM and Hs-CRP ≤3 mg/L, and the DM(+)CRP(+) group defined as presence of DM and Hs-CRP >3 mg/L. The data of participants were collected by a fixed team of physicians. The first physical examination in 2006 was taken as the starting point for follow-up. The end event of follow-up was defined as the occurrence of digestive system malignancy or death, and the follow-up was up to December 31, 2021. Observation indicators: (1) comparison of clinical data among the 4 groups of participants; (2) the incidence and cumulative incidence rate of digestive system malignancy in participants; (3) influence of DM and Hs-CRP level on the risk of digestive system malignancy; (4) the combined influence of DM and Hs-CRP level on the risk of digestive system malignancy; (5) sensitivity analysis. Comparison of measurement data with normal distribution among multiple groups was conducted using the one-way analysis of variance. For pairwise comparison, least significant difference test was used for homogeneity of variance, and Dunnett′s T3 test was used for heterogeneity of variance. Comparison of measurement data with skewed distribution among multiple groups was conducted using the Kruskal-Wallis rank sum test, and Dunn-Bonferroni test was used for pairwise comparison. Comparison of count data among multiple groups was conducted using the chi-square test, and Bonferroni test was used among multiple comparisons. The Kaplan-Meier method was used to plot cumulative incidence curve, and Log-rank test was used for cumulative incidence rate analysis. The Cox proportional risk model was used for multivariate analysis. All models were adjusted for relevant confounders. Results:(1) Comparison of clinical data among the 4 groups of participants. Of the 93 928 participants, there were 70 743 cases in the DM(-)CRP(-) group, 14 644 cases in the DM(-)CRP(+) group, 6 425 cases in the DM(+)CRP(-) group, and 2 116 cases in the DM(+)CRP(+) group. There were significant differences in gender, age, fasting blood glucose, Hs-CRP, triglyceride, alanine aminotransferase, body mass index, marrital status, smoking, drinking, high school degree or above, physical exercise, high salt diet, high fat diet, positive hepatitis B virus surface antigen, fatty liver, liver cirrhosis, gallstone, taking hypoglycemic drugs, taking lipid-lowering drugs among the 4 groups of participants ( P<0.05). (2) The incidence and cumulative incidence rate of digestive system malignancy in participants. At the end-up of follow-up, 2 008 cases developed digestive system malignancy in the 93 928 participants, including 717 cases of colorectal cancer, 456 cases of liver cancer, 396 cases of gastric cancer, 195 cases of esophageal cancer, 144 cases of pancreatic cancer, 65 cases of gallbladder cancer or extrahepatic cholangiocarcinoma, 35 cases of small bowel cancer. The cumulative incidence rates of digestive system malignancy were 2.19%, 2.42%, 2.86%, 3.59% in participants of the DM(-)CRP(-) group, DM(-)CRP(+) group, DM(+)CRP(-) group, DM(+)CRP(+) group, respectively, showing a significant difference among the 4 groups ( χ2=31.72, P<0.05). (3) Influence of DM and Hs-CRP level on the risk of digestive system malignancy. After adjusting for the confounding factors of the participants, results of multivariate analysis showed that DM and Hs-CRP >3 mg/L were independent influencing factors for the incidence of digestive system malignancy ( hazard ratio=1.32, 1.19, 95% confidence interval as 1.13-1.56, 1.06-1.33, P<0.05). Futher analysis showed that there was a significant difference in interaction between DM and Hs-CRP >3 mg/L ( P<0.05). (4) The combined influence of DM and Hs-CRP level on the risk of digestive system malign-ancy. After adjusting for confounding factors, results of multivariate analysis showed that using the DM(-)CRP(-) group as the control group, the risk of incidence of digestive system malignancy increased in the DM(-)CRP(+) group, DM(+)CRP(-) group, and DM(+)CRP(+) group, respectively ( hazard ratio=1.14, 1.23, 1.79, 95% confidence interval as 1.01-1.29, 1.02-1.48, 1.38-2.31, P<0.05). In the site-specific analysis of digestive system malignancy, using the DM(-)CRP(-) group as the control group, the risk of incidence of liver cancer increased in the DM(-)CRP(+) group ( hazard ratio=1.37, 95% confidence interval as 1.07-1.75, P<0.05), the risk of incidence of liver cancer and pancrea-tic cancer increased in the DM(+)CRP(-) group ( hazard ratio=1.60, 1.74, 95% confidence interval as 1.16-2.21, 1.00-3.02, P<0.05), the risk of incidence of small bowel cancer, pancreatic cancer and colorectal cancer increased in the DM(+)CRP(+) group ( hazard ratio=5.05, 2.31, 2.23, 95% confidence interval as 1.57-16.21, 1.00-5.31, 1.54-3.24, P<0.05). (5) Sensitivity analysis. After adjusting for confounding factors of excluding 3 types of participants (103 cases of digestive system malignancy within 1 year of follow-up, 2 370 cases of taking glucose-lowering drugs, and 915 cases of taking lipid-lowering drugs), results of multivariate analysis showed that using the DM(-)CRP(-) group as the control group, the risk of incidence of digestive system malignancy increased in the DM(+)CRP(-) group, and DM(+)CRP(+) group, respectively ( hazard ratioexcluding cases of digestive system malignancy within 1 year of follow-up=1.26, 1.66, 95% confidence interval as 1.04-1.52, 1.26-2.18, P<0.05; hazard ratioexcluding cases taking glucose-lowering drugs=1.23, 1.75, 95% confidence interval as 1.02-1.49, 1.31-2.33, P<0.05; hazard ratioexcluding cases taking lipid-lowering drugs=1.24, 1.80, 95% confidence interval as 1.03-1.49, 1.39-2.34, P<0.05). Conclusions:DM and Hs-CRP >3 mg/L are independent influencing factors for the incidence of digestive system malignancy. There is an interation and synergistic effect between DM and Hs-CRP to promote the incidence of digestive system malignancy.
6.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; 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(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
7.Epimedokoreanin B induces pyroptosis in HepaRG cells through NLRP1/caspase-1/GSDMD signaling pathway
Yu-tong DONG ; Hao-ran HU-YAN ; Li-zhen QIU ; Chao MA ; Shao-xia WANG ; Kun ZHOU
Chinese Pharmacological Bulletin 2025;41(11):2053-2057
Aim To explore the role and mechanism of epimedokoreanin B(EKB)in HepaRG cell pyroptosis through endoplasmic reticulum stress and NLRP1-me-diated pyroptosis pathway.Methods The effect of EKB on the viability of HepaRG cells at different con-centrations was determined by MTT assay,and the cell growth status was recorded by Incucyte.Four groups of HepaRG cells were set up.The control group was cul-tured with complete medium for 24 h;the drug admin-istration group was cultured with three concentration gradients of 6.25,12.5 and 25 μmol·L-1 of EKB for 24 h.Western blot was used to detect the expression levels of endoplasmic reticulum stress-related proteins and pyroptosis-related proteins in the cells of each group.Results HepaRG cells showed cytotoxicity at a concentration of 6.25 μmol·L-1 for 24 h,and the half maximal inhibitory concentration(IC50)was 12.41 μmol·L-1.Incucyte recordings of the cell growth status showed that the cells in the control group were in good growth status,and the vesicular pyropto-sis cells appeared in the different concentrations of EKB and the cells swelled and ruptured after 24 h.Western blot showed that the protein expression levels of endoplasmic reticulum stress-related proteins pERK,eIF-2α,ATF-4,GRP78,and CHOP significantly in-creased in HepaRG cells at 25 μmol·L-1 of EKB compared with the control group.The proteins of the classical pathway of cellular pyroptosis mediated by NLRP1,caspase-1,cleaved caspase-1,GSDMD,GS-DMD-N significantly increased in HepaRG cells.Con-clusion EKB administration induces HepaRG cell py-roptosis,and EKB activates HepaRG cells to undergo endoplasmic reticulum stress and activates the NLRP1/caspase-1/GSDMD-mediated pyroptosis pathway.
8.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; 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(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
9.Screening and validation of glucose metabolism genes in osteoarthritis
Kexin LIU ; Chao MA ; Kai LIU ; Maochen HAO ; Xingru WANG ; Lingting MENG ; Mei DONG ; Jianzhong WANG
Chinese Journal of Tissue Engineering Research 2025;29(20):4181-4189
BACKGROUND:Glucose metabolism plays a crucial role in maintaining the normal physiological function of the body.Glucose metabolism disorder can lead to a range of health problems.At present,the molecular mechanism of glucose metabolism and potential gene targets in osteoarthritis need to be further studied.OBJECTIVE:To analyze the genes related to glucose metabolism in osteoarthritis by bioinformatics methods,and to verify them by cell experiments in vitro,so as to provide new ideas for prevention and treatment of osteoarthritis from the perspective of glucose metabolism.METHODS:Differentially expressed genes and glucose metabolism related genes were screened out from GEO database and GeneCards database.The genes related to both osteoarthritis and glucose metabolism were obtained.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were used to screen the functions and pathways of these genes.To further investigate the interactions between these genes,a protein-protein interaction network was constructed and computational methods using Cytoscape software were utilized to identify key genes(Hub genes)for osteoarthritis glucose metabolism.In addition,CIBERSORT algorithm was used to analyze immune cell infiltration in GSE98918 data set.Finally,the expression of Hub gene was verified by cell experiment in vitro.RESULTS AND CONCLUSION:A total of 134 osteoarthritis glucose metabolism-related genes were obtained.GO enrichment analysis showed that GO was mainly involved in the reaction of toxic substances,the positive regulation of inflammatory reaction,the reaction of lipopolysaccharide and so on.KEGG enrichment analysis showed that it was closely related to PI3K-Akt signaling pathway,interleukin-17 signaling pathway,and AGE-RAGE signaling pathway in diabetic complications.Macrophages,monocytes,resting natural killer cells,regulatory T cells,and CD8+T cells were the main infiltrating cells obtained by immune infiltration analysis.In vitro cell experiments showed that the expression of Hub genes SERPINF1,TAC1,GLUL,APOE,and TMEM176A in the experimental group was significantly different from that in the control group.The mRNA expression of HLA-DRA was not statistically significant.The results show that SERPINF1,TAC1,Glul,APOE,and TMEM176A may be the key genes of glucose metabolism in osteoarthritis,and may be potential new targets for the prevention and treatment of osteoarthritis.
10.Predictive value of different obesity indicators for colorectal cancer in different sex populations
Chao MA ; Jiaxing LI ; Kuan LIU ; Wanchao WANG ; Yuan TIAN ; Taixian JIANG ; Zhigang DONG ; Wenqiang WEI ; Shouling WU ; Siqing LIU
Chinese Journal of Gastrointestinal Surgery 2025;28(1):75-80
Objective:To investigate the predictive value of different obesity indicators for colorectal cancer (CRC) risk in different gender populations.Methods:This observational study was conducted within the Kailuan Study (Registration Number: ChiCTR-TNC-11001489). From July 2006 to October 2007, a total of 101,510 employed and retired individuals underwent health examinations, including gastrointestinal disease screening, hematological tests, and questionnaires, at Kailuan General Hospital and its 10 affiliated hospitals. After excluding those with incomplete data, 93,606 participants were included in this study and divided into male (74 852) and female (18 754) groups. CRC incidence was collected through physical examinations and questionnaires every two years. Each participant's follow-up period began at the time of the questionnaire and ended upon CRC diagnosis, death, or December 31, 2021. Body Mass Index (BMI), waist circumference, waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) were quartiled (Q1, Q2, Q3, Q4), with Q1 serving as the control group. After adjusting for traditional risk factors such as age, total cholesterol, triglycerides, diabetes, hypertension, smoking status, alcohol consumption, and physical exercise, Cox regression models were used to calculate the correlations between BMI, waist circumference, WHR, WHtR, and CRC incidence in both male and female populations.Results:The age of all patients was (51±12) years, BMI was (25.06±3.49) kg/m 2, waist circumference was (86.94±9.97) cm, hip circumference was (97.30±8.81) cm, WHR was 0.89±0.07, and WHtR was 0.52±0.06.Female participants had significantly lower BMI, waist circumference, WHR, and WHtR compared to males, with statistically significant differences (all P<0.05). The mean follow-up duration for all participants was 15.01 (14.10±2.66) years, during which 718 CRC cases were identified, including 626 males (0.83%) and 92 females (0.49%). Cox proportional hazards models for males showed that CRC risk increased with waist circumference from Q3 (HR=1.43, 95%CI: 1.13-1.79, P=0.003) to Q4 (HR=1.45,95%CI: 1.14-1.82, P=0.002). Similarly, CRC risk increased with WHR from Q3 (HR=1.22, 95%CI: 1.01-1.53, P=0.007) to Q4 (HR=1.43, 95%CI: 1.14-1.79, P=0.002) and with WHtR from Q3 (HR=1.37, 95%CI: 1.08-1.74, P=0.009) to Q4 (HR=1.68, 95%CI: 1.33-2.12, P<0.001). For females, CRC risk increased with waist circumference from Q2 (HR=2.37, 95%CI: 1.20-4.67, P=0.012) to Q3 (HR=2.42, 95%CI: 1.21-4.84, P=0.013) but decreased in Q4 ( HR=2.08, 95%CI: 1.02-4.25, P=0.043). CRC risk increased significantly with WHR from Q2 (HR=2.20, 95%CI: 1.11-4.39, P=0.024) to Q3 (HR=2.89, 95%CI: 1.48-5.67, P=0.002) in females but was not statistically significant in Q4 ( P=0.074). Among females, CRC risk also increased significantly with WHtR in Q2 (HR=2.30, 95% CI: 1.16-4.56, P=0.017) and Q4 (HR=2.64, 95%CI: 1.32-5.29, P=0.006). There were no statistically significant differences in CRC risk associated with BMI in either male or female populations (both P>0.05). Conclusion:Waist circumference, WHR, and WHtR were better predictors of CRC risk than BMI in both male and female populations.

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