1.Clinical Efficacy of Xiaoji Hufei Formula in Protecting Children with Close Contact Exposure to Influenza: A Multicenter,Prospective, Non-randomized, Parallel, Controlled Trial
Jing WANG ; Jianping LIU ; Tiegang LIU ; Hong WANG ; Yingxin FU ; Jing LI ; Huaqing TAN ; Yingqi XU ; Yanan MA ; Wei WANG ; Jia WANG ; Haipeng CHEN ; Yuanshuo TIAN ; Yang WANG ; Chen BAI ; Zhendong WANG ; Qianqian LI ; He YU ; Xueyan MA ; Fei DONG ; Liqun WU ; Xiaohong GU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(21):223-230
ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza, and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter, prospective, non-randomized, parallel, controlled trial was conducted from October 2021 to May 2022 in five hospitals, including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness (ILI) cases were collected, and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention, they were assigned to the observation group (108 cases) or the control group (108 cases). Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine (TCM) symptom score scale for influenza, influenza-related emergency (outpatient) visit rate, influenza hospitalization rate, and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled, with 108 in the observation group and 108 in the control group. Primary outcomes: (1) Incidence of ILI: The incidence was 12.0% (13/108) in the observation group and 23.1% (25/108) in the control group, with the observation group showing a significantly lower incidence (χ2=4.6, P<0.05). (2) Influenza confirmation rate: 3.7% (4/108) in the observation group and 4.6% (5/108) in the control group, with no statistically significant difference. Secondary outcomes: (1) TCM symptom score scale: after onset, nasal congestion and runny nose scores differed significantly between the two groups (P<0.05), while other symptoms such as fever, sore throat, and cough showed no significant differences. (2) Influenza-related emergency (outpatient) visit rate: 84.6% (11 cases) in the observation group and 96.0% (24 cases) in the control group, with no significant difference. (3) Time to onset after exposure: The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group, with a statistically significant difference (P<0.05). ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions, Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.
2.Clinical Efficacy of Xiaoji Hufei Formula in Protecting Children with Close Contact Exposure to Influenza: A Multicenter,Prospective, Non-randomized, Parallel, Controlled Trial
Jing WANG ; Jianping LIU ; Tiegang LIU ; Hong WANG ; Yingxin FU ; Jing LI ; Huaqing TAN ; Yingqi XU ; Yanan MA ; Wei WANG ; Jia WANG ; Haipeng CHEN ; Yuanshuo TIAN ; Yang WANG ; Chen BAI ; Zhendong WANG ; Qianqian LI ; He YU ; Xueyan MA ; Fei DONG ; Liqun WU ; Xiaohong GU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(21):223-230
ObjectiveTo evaluate the efficacy and safety of Xiaoji Hufei Formula in protecting children with close contact exposure to influenza, and to provide reference and evidence-based support for better clinical prevention and treatment of influenza in children. MethodsA multicenter, prospective, non-randomized, parallel, controlled trial was conducted from October 2021 to May 2022 in five hospitals, including Dongfang Hospital of Beijing University of Chinese Medicine. Confirmed influenza cases and influenza-like illness (ILI) cases were collected, and eligible children with close contact exposure to these cases were recruited in the outpatient clinics. According to whether the enrolled close contacts were willing to take Xiaoji Hufei formula for influenza prevention, they were assigned to the observation group (108 cases) or the control group (108 cases). Follow-up visits were conducted on days 7 and 14 after enrollment. The primary outcomes were the incidence of ILI and the rate of laboratory-confirmed influenza. Secondary outcomes included traditional Chinese medicine (TCM) symptom score scale for influenza, influenza-related emergency (outpatient) visit rate, influenza hospitalization rate, and time to onset after exposure to influenza cases. ResultsA total of 216 participants were enrolled, with 108 in the observation group and 108 in the control group. Primary outcomes: (1) Incidence of ILI: The incidence was 12.0% (13/108) in the observation group and 23.1% (25/108) in the control group, with the observation group showing a significantly lower incidence (χ2=4.6, P<0.05). (2) Influenza confirmation rate: 3.7% (4/108) in the observation group and 4.6% (5/108) in the control group, with no statistically significant difference. Secondary outcomes: (1) TCM symptom score scale: after onset, nasal congestion and runny nose scores differed significantly between the two groups (P<0.05), while other symptoms such as fever, sore throat, and cough showed no significant differences. (2) Influenza-related emergency (outpatient) visit rate: 84.6% (11 cases) in the observation group and 96.0% (24 cases) in the control group, with no significant difference. (3) Time to onset after exposure: The median onset time after exposure to index patients was 7 days in the observation group and 4 days in the control group, with a statistically significant difference (P<0.05). ConclusionIn previously healthy children exposed to infectious influenza cases under unprotected conditions, Xiaoji Hufei formula prophylaxis significantly reduced the incidence of ILI. Xiaoji Hufei Formula can be recommended as a specific preventive prescription for influenza in children.
3.Diagnostic Techniques and Risk Prediction for Cardiovascular-kidney-metabolic (CKM) Syndrome
Song HOU ; Lin-Shan ZHANG ; Xiu-Qin HONG ; Chi ZHANG ; Ying LIU ; Cai-Li ZHANG ; Yan ZHU ; Hai-Jun LIN ; Fu ZHANG ; Yu-Xiang YANG
Progress in Biochemistry and Biophysics 2025;52(10):2585-2601
Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.
4.Relationship between FGFR2 gene polymorphisms rs3135718 and rs1219648 with breast cancer risk and protein expression in Chinese women
Fu-rong HUANG ; Yang LIU ; Hong REN ; Yong-dong JIANG
Chinese Journal of Current Advances in General Surgery 2025;28(5):350-354
Objective:To investigate the relationship between fibroblast growth factor receptor-2(FGFR2)gene polymorphisms and the risk of breast cancer and its protein expression in Han women from Heilongjiang,China.Meth-ods:Using the Snapshot technique for multiplex single nucleotide polymorphism genotyping,the polymorphisms rs3135718 and rs1219648 of FGFR2 were analyzed in 747 breast cancer patients and 716 healthy controls.Logistic re-gression was used to examine the association between these genotypes and breast cancer susceptibility.In a subset of 338 cases,immunohistochemistry was performed to assess FGFR2 protein expression,and chi-square tests was used to analyze the relationship between polymorphisms and protein expression.Results:The genotype frequencies of FGFR2 rs3135718 and rs1219648 showed significant differences between the breast cancer and control group.Logistic regression revealed that,for rs3135718,the CT,CC,and CT+CC genotypes were associated with increased breast cancer risk compared to the TT genotype(OR=1.280,95%CI:1.003-1.633;OR=1.500,95%CI:1.112-2.023;OR=1.341,95%CI:1.066-1.688).For rs1219648,the GA,GG,and GA+GG genotypes were significantly associated with higher breast cancer risk compared to the AA genotype(OR=1.352,95%CI:1.063-1.719;OR=1.826,95%CI:1.361-2.504;OR=1.475,95%CI:1.175-1.852).However,no significant association was found between FGFR2 rs3135718 and rs1219648 polymorphisms and FGFR2 protein expression(χ2=0.052,P=0.820;χ2=0.117,P=0.732).Conclusion:FGFR2 gene poly-morphisms rs3135718 and rs1219648 are significantly associated with breast cancer susceptibility in Han women from Heilongjiang,China,but these polymorphisms do not show a clear relationship with FGFR2 protein expression.
5.Distribution and resistance profiles of bacterial strains isolated from cerebrospinal fluid in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Juan MA ; Lixia ZHANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Han SHEN ; Wanqing ZHOU ; Wenen LIU ; Yanming LI ; Yi XIE ; Mei KANG ; Dawen GUO ; Jinying ZHAO ; Zhidong HU ; Jin LI ; Shanmei WANG ; Yafei CHU ; Yunsong YU ; Jie LIN ; Yingchun XU ; Xiaojiang ZHANG ; Jihong LI ; Bin SHAN ; Yan DU ; Ping JI ; Fengbo ZHANG ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Xiaobo MA ; Yanping ZHENG ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Hua YU ; Xiangning HUANG ; Sufang GUO ; Xuesong XU ; Chao YAN ; Fangfang HU ; Yan JIN ; Chunhong SHAO ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Fang DONG ; Zhiyong LÜ ; Lei ZHU ; Jinhua MENG ; Shuping ZHOU ; Yan ZHOU ; Chuanqing WANG ; Pan FU ; Yunjian HU ; Xiaoman AI ; Ziyong SUN ; Zhongju CHEN ; Hong ZHANG ; Chun WANG ; Yuxing NI ; Jingyong SUN ; Kaizhen WEN ; Yirong ZHANG ; Ruyi GUO ; Yan ZHU ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Shifu WANG ; Yunsheng CHEN ; Qing MENG ; Yong ZHAO ; Ping GONG ; Ruizhong WANG ; Hua FANG ; Jilu SHEN ; Jiangshan LIU ; Hongqin GU ; Jiao FENG ; Shunhong XUE ; Bixia YU ; Wen HE ; Lin JIANG ; Longfeng LIAO ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):279-289
Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3%)and from outpatient and emergency care patients(4.7%).Overall,19.6%of the isolates were from children and 80.4%were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0%and 32.0%,respectively.Coagulase negative Staphylococcus accounted for 73.0%of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2%in children and 45.6%in adults.The prevalence of MRCNS was 67.6%in adults and 69.5%in children.A small number of vancomycin-resistant Enterococcus faecium(2.2%)and linezolid-resistant Enterococcus faecalis(3.1%)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2%and 76.4%in children,70.5%and 63.5%in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3%and 47.7%in children,6.4%and 47.9%in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0%and 37.1%in children,81.7%and 39.9%in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.
6.Changing antibiotic resistance profiles of the bacterial strains isolated from geriatric patients in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Xiaoman AI ; Yunjian HU ; Chunyue GE ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(3):290-302
Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3%of the total number of clinical isolates from all patients.Overall,21.8%of the 514 715 strains were gram-positive bacteria,and 78.2%were gram-negative bacteria.Majority(90.9%)of the strains were isolated from inpatients.About 42.9%of the strains were isolated from respiratory specimens,and 22.9%were isolated from urine.More than half(60.7%)of the strains were isolated from male patients,and 39.3%isolated from females.About 51.1%of the strains were isolated from patients aged 65-<75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8%in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2%,1.5%)and linezolid-resistant strains(3.4%,0.3%)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3%,4.0%,and 1.7%in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2%)to imipenem and meropenem were 20.9%and 22.3%,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7%-7.8%of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6%)to imipenem and meropenem were 68.4%and 70.6%respectively,while 28.5%and 24.3%of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-<75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.
7.Antimicrobial resistance surveillance in the bacterial strains isolated from pediatric intensive care units in China:results from 2020 to 2022
Jing LIU ; Huiyuan YAN ; Gangfeng YAN ; Guoping LU ; Pan FU ; Chuanqing WANG ; Danqun JIN ; Wenjia TONG ; Chenyu ZHANG ; Jianli CHEN ; Yi LIN ; Jia LEI ; Yibing CHENG ; Qunqun ZHANG ; Kaijie GAO ; Yuanyuan CHEN ; Shufang XIAO ; Juan HE ; Li JIANG ; Huimin XU ; Yuxia LI ; Hanghai DING ; Hehe CHEN ; Yao ZHENG ; Qunying CHEN ; Ying WANG ; Hong REN ; Chenmei ZHANG ; Zhenjie CHEN ; Mingming ZHOU ; Yucai ZHANG ; Yiping ZHOU ; Zhenjiang BAI ; Saihu HUANG ; Lili HUANG ; Weiguo YANG ; Weike MA ; Qing MENG ; Pengwei ZHU ; Yong LI ; Yan XU ; Yi WANG ; Yanqiang DU ; Huijun CAI ; Bizhen ZHU ; Huixuan SHI ; Shaoxian HONG ; Yukun HUANG ; Meilian HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):303-311
Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2%)and gram-negative organisms(60.8%).The top three organisms were S.aureus(13.6%,1 453/10 688),A.baumannii(10.0%,1 067/10 688),and coagulase-negative Staphylococcus(9.9%,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1%,19.4%,8.8%,30.9%,67.4%,and 28.8%,respectively.Overall,more than 50%of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25%of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80%of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3%in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.
8.Clinical features of chronic hepatitis C patients with genotype 3 infection:A multicenter retrospective cohort study
Jingyi XIE ; Yujia JING ; Yishan LIU ; Manling BAI ; Zhangqian CHEN ; Qiang XU ; Hong DU ; Yuxiu MA ; Liting ZHANG ; Shanshan ZHU ; Xiaoqin GAO ; Xinggang BAI ; Guoying YU ; Jianqi LIAN ; Xiaozhong WANG ; Yongping ZHANG ; Jiuping WANG ; Fanpu JI ; Jianjun FU ; Ning GAO
Journal of Clinical Hepatology 2025;41(8):1533-1540
Objective To investigate the clinical features of chronic hepatitis C(CHC)patients with hepatitis C virus genotype 3(HCV GT3)infection and the risk factors for disease progression.Methods A multicenter retrospective cohort study was conducted among 1 002 CHC patients from 11 clinical centers in Northwest China from December 2017 to November 2023,and according to their genotype,they were divided into GT1,GT2,GT3,and GT6 groups.Clinical features were compared between the patients with different genotypes.The one-way analysis of variance was used for comparison of normally distributed continuous data between groups,and the Scheffe test was used for further comparison between two groups.The Kruskal-Wallis H test was used for comparison of data with skewed distribution between groups;the chi-square test or Fisher test was used for comparison of categorical data between groups.The multivariate logistic regression analysis was used to explore the influencing factors for the progression of CHC to liver cirrhosis.Results In terms of the genotype,there were 427 patients with GT1 infection,242 with GT2 infection,299 with GT3 infection(210 patients with GT3a infection,87 with GT3b infection,and 2 with unclassified genotype),and 34 with GT6 infection.The patients with GT3 infection had a significantly younger age than those with GT1 infection(51.3±0.5 years vs 53.2±0.6 years,P<0.05)or GT2 infection(51.3±0.5 years vs 53.7±0.8 years,P<0.05),and for the patients with liver cirrhosis,the patients with GT3 infection had a significantly younger age than those with GT1 infection(52.1±0.5 years vs 59.4±0.9 years,P<0.001)or GT2 infection(52.1±0.5 years vs 58.1±1.1 years,P<0.001).Among the patients with GT3 infection,male patients accounted for 77.9%and the patients with liver cirrhosis accounted for 46.2%,which were significantly higher than those among the patients with GT1,GT2 or GT6 infection(all P<0.001).At baseline,the patients with GT3 infection had significantly higher levels of alanine aminotransferase(ALT)and aspartate aminotransferase(AST)than those with GT1 or GT2 infection,significantly higher aspartate aminotransferase-to-platelet ratio index(APRI)and fibrosis-4(FIB4)than those with GT1,GT2 or GT6 infection,a significantly lower platelet count(PLT)than those with GT2 or GT6 infection,a significantly higher level of alpha-fetoprotein than those with GT2 or GT6 infection,and a significantly lower level of albumin(Alb)than those with GT6 infection(all P<0.05).There were no significant differences between the patients with GT3a infection and those with GT3b infection in age,sex,the proportion of patients with liver cirrhosis,comorbidities,HCV RNA quantification,PLT,ALT,AST,alkaline phosphatase,Alb,APRI,and FIB-4(all P>0.05).The multivariate logistic regression analysis showed that PLT≤150×109/L(odds ratio[OR]=10.72,95%confidence interval[CI]:5.76-35.86,P<0.001)and Alb≤35 g/L(OR=3.74,95%CI:1.22-11.45,P=0.021)were risk factors for liver cirrhosis.Conclusion Most CHC patients with GT3 infection are male in Northwest China,and compared with the patients with other genotypes,such patients tend to have a younger age of onset and higher degrees of liver inflammation activity and fibrosis.Low PLT and a low level of Alb are risk factors for progression to liver cirrhosis in CHC patients with GT3 infection.
9.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.
10.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.

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