1.Expression and clinical significance of serum CXCL1 and PRDM5 in lymph node metastasis of progressive gastric cancer
Xiaoying DING ; Zhichao DONG ; Jianna MAO ; Changqing GUO ; Aimin YUE
The Journal of Practical Medicine 2025;41(20):3206-3213
Objective To investigate the relationship between serum CXC chemokine ligand 1(CXCL1)and positive regulatory zone zinc finger protein 5(PRDM5)levels and lymph node metastasis of progressive gastric cancer and to analyze their predictive value for patients'prognosis.Methods 203 patients with progressive gastric cancer diagnosed in our hospital from June 2020 to March 2023 were selected and divided into the lymph node metastasis group(n=90)and the no-lymph node metastasis group(n=113)based on the presence or absence of lymph node metastasis,and the differences in the general information of the two groups were analyzed and compared,and the diagnostic value of CXCL1 and PRDM5 in lymph node metastasis of progressive gastric cancer was analyzed by plotting the ROC curve.Logistic regression was used to analyze the risk factors of lymph node metastasis in patients with progressive gastric cancer.Follow up for 2 years,draw Kapan Meier curves to compare the prognosis of patients with advanced gastric cancer lymph node metastasis at different levels of CXCL1 and PRDM5.Results The CXCL1 level in the lymph node metastasis group was higher than that in the no-lymph node metastasis group,and its PRDM5 level was lower than that in the no-lymph node metastasis group(P<0.05).The AUCs for diagnosing lymph node metastasis of progressed gastric cancer were 0.755 and 0.844 for CXCL1 and PRDM5,respectively,and the AUC for the combination of the two was 0.898(95%CI 0.848~0.936).The sensitivity and specificity were 88.89%and 77.88%,respectively(P<0.05).Tumor size,differentation degree,serum CEA,serum CA19-9,CXCL1,and PRDM5 levels were all risk factors for lymph node metastasis in patients with progressive gastric cancer(P<0.05).The survival time of patients with CXCL1>96.13 pg/mL is(15.13±0.85)months,while the survival time of patients with CXCL1≤96.13 pg/mL is(19.06±0.66)months.The survival time of patients with CXCL1≤96.13 pg/mL is longer than that of patients with CXCL1>96.13 pg/mL(P<0.05).The survival time of patients with PRDM>100.85 pg/mL is(18.62±0.69)months,while the survival time of patients with PRDM≤100.85 pg/mL is(14.60±0.78)months.The survival time of patients with PRDM>100.85 pg/mL is longer than that of patients with PRDM≤100.85 pg/mL(P<0.05).Conclusion The abnormal expression of CXCL1 and PRDM5 is related to lymph node metastasis in patients with progressive gastric cancer,and the combined detection of the two is of high value in the assessment of lymph node metastasis and prognosis in patients with progressive gastric cancer.
2.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
3.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.
4.Expression and clinical significance of serum CXCL1 and PRDM5 in lymph node metastasis of progressive gastric cancer
Xiaoying DING ; Zhichao DONG ; Jianna MAO ; Changqing GUO ; Aimin YUE
The Journal of Practical Medicine 2025;41(20):3206-3213
Objective To investigate the relationship between serum CXC chemokine ligand 1(CXCL1)and positive regulatory zone zinc finger protein 5(PRDM5)levels and lymph node metastasis of progressive gastric cancer and to analyze their predictive value for patients'prognosis.Methods 203 patients with progressive gastric cancer diagnosed in our hospital from June 2020 to March 2023 were selected and divided into the lymph node metastasis group(n=90)and the no-lymph node metastasis group(n=113)based on the presence or absence of lymph node metastasis,and the differences in the general information of the two groups were analyzed and compared,and the diagnostic value of CXCL1 and PRDM5 in lymph node metastasis of progressive gastric cancer was analyzed by plotting the ROC curve.Logistic regression was used to analyze the risk factors of lymph node metastasis in patients with progressive gastric cancer.Follow up for 2 years,draw Kapan Meier curves to compare the prognosis of patients with advanced gastric cancer lymph node metastasis at different levels of CXCL1 and PRDM5.Results The CXCL1 level in the lymph node metastasis group was higher than that in the no-lymph node metastasis group,and its PRDM5 level was lower than that in the no-lymph node metastasis group(P<0.05).The AUCs for diagnosing lymph node metastasis of progressed gastric cancer were 0.755 and 0.844 for CXCL1 and PRDM5,respectively,and the AUC for the combination of the two was 0.898(95%CI 0.848~0.936).The sensitivity and specificity were 88.89%and 77.88%,respectively(P<0.05).Tumor size,differentation degree,serum CEA,serum CA19-9,CXCL1,and PRDM5 levels were all risk factors for lymph node metastasis in patients with progressive gastric cancer(P<0.05).The survival time of patients with CXCL1>96.13 pg/mL is(15.13±0.85)months,while the survival time of patients with CXCL1≤96.13 pg/mL is(19.06±0.66)months.The survival time of patients with CXCL1≤96.13 pg/mL is longer than that of patients with CXCL1>96.13 pg/mL(P<0.05).The survival time of patients with PRDM>100.85 pg/mL is(18.62±0.69)months,while the survival time of patients with PRDM≤100.85 pg/mL is(14.60±0.78)months.The survival time of patients with PRDM>100.85 pg/mL is longer than that of patients with PRDM≤100.85 pg/mL(P<0.05).Conclusion The abnormal expression of CXCL1 and PRDM5 is related to lymph node metastasis in patients with progressive gastric cancer,and the combined detection of the two is of high value in the assessment of lymph node metastasis and prognosis in patients with progressive gastric cancer.
5.Changing distribution and antimicrobial resistance profiles of clinical isolates in children:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Qing MENG ; Lintao ZHOU ; Yunsheng CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Chuanqing WANG ; Aimin WANG ; Lei ZHU ; Jinhua MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Zhiyong LÜ ; Shuping ZHOU ; Yan ZHOU ; Shifu WANG ; Fangfang HU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Wei JIA ; Gang LI ; Kaizhen WEN ; Yirong ZHANG ; Yan JIN ; Chunhong SHAO ; Yong ZHAO ; Ping GONG ; Chao ZHUO ; Danhong SU ; Bin SHAN ; Yan DU ; Sufang GUO ; Jiao FENG ; Ziyong SUN ; Zhongju CHEN ; Wen'en LIU ; Yanming LI ; Xiaobo MA ; Yanping ZHENG ; Dawen GUO ; Jinying ZHAO ; Ruizhong WANG ; Hua FANG ; Lixia ZHANG ; Juan MA ; Jihong LI ; Zhidong HU ; Jin LI ; Yuxing NI ; Jingyong SUN ; Ruyi GUO ; Yan ZHU ; Yi XIE ; Mei KANG ; Yuanhong XU ; Ying HUANG ; Shanmei WANG ; Yafei CHU ; Hua YU ; Xiangning HUANG ; Lianhua WEI ; Fengmei ZOU ; Han SHEN ; Wanqing ZHOU ; Yunzhuo CHU ; Sufei TIAN ; Shunhong XUE ; Hongqin GU ; Xuesong XU ; Chao YAN ; Bixia YU ; Jinju DUAN ; Jianbang KANG ; Jiangshan LIU ; Xuefei HU ; Yunsong YU ; Jie LIN ; Yunjian HU ; Xiaoman AI ; Chunlei YUE ; Jinsong WU ; Yuemei LU
Chinese Journal of Infection and Chemotherapy 2025;25(1):48-58
Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1%of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9%)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5%)was lower than that in inpatient children(31.5%).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1%)than in inpatient children(59.4%).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14%,11.7%,47.8%in outpatients,but 24.2%,20.6%,and 52.8%in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.
6.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.
7.The impact of body constitutional metabolic phenotype on the outcomes of hypertensive intracerebral hemorrhage patients one year after onset.
Yue ZHANG ; Zhiwei XU ; Yuxin LI ; Dapeng DAI ; Aimin LI
Clinical Medicine of China 2025;41(3):175-181
Objective:To explore the impact of body constitutional metabolic phenotype on the outcomes of hypertensive intracerebral hemorrhage (HICH) patients one year after onset.Methods:This study retrospectively studied the clinical data of 467 HICH patients admitted to the First People's Hospital of Lianyungang City from May 2021 to May 2023. Based on telephone follow-up after one year, the patients were categorized into two groups: a good outcome group (287 cases) and a poor outcome group (180 cases). According to the patients' body mass index (BMI) and metabolic status, the population was divided into six phenotypes: metabolically healthy with normal weight (MH-NW), metabolically healthy with overweight (MH-OW), metabolically healthy obesity (MHO), metabolically unhealthy normal weight (MU-NW), metabolically unhealthy with overweight (MU-OW), and metabolically unhealthy with obesity (MUO). The baseline data of the two groups were compared between two groups. The influencing factors of adverse outcomes in patients with HICH one year after onset were analyzed. Quantitative data that conforms to normal distribution were represented by xˉ±s, and independent sample t-test was used for comparison between two groups; The measurement data of skewed distribution was represented by M ( Q1, Q3), and Mann Whitney U test was used for comparison between the two groups; Count data was presented as an example (%), and comparison between groups was conducted using the χ2 test. Multivariate logistic regression analysis was used to analyze the influencing factors of poor prognosis in HICH patients one year after onset. Results:BMI, high density lipoprotein cholesterol(HDL-C) levels and baseline Glasgow coma score(GCS) score in the poor outcome group were lower than those in the good outcome group [23.8 (22.4, 26.1) kg/m 2 vs. 25.0 (22.5, 27.4) kg/m 2, Z=-2.31, P=0.021; 1.1 (1.0,1.4) mmol/L vs. 1.3 (1.0,1.6) mmol/L, Z=-4.18, P<0.001; 14 (13,15) score vs. 10 (7,13) score, Z=-10.20, P<0.001]. The incidence of hemorrhage into the ventricle, cerebral hernia, pulmonary infection and hydrocephalus [43.3%(78/180) vs. 23.7% (68/287). 5.6%(10/180) vs. 0.7% (2/287), 48.9%(88/180) vs. 6.6% (19/287), 5.0%(9/180) vs. 1.4% (4/287), χ2=19.86, P<0.001, χ2=10.43, P<0.001, χ2=111.90, P<0.001, χ2=5.32, P=0.021], proportion of surgical removal of hematoma [41.1%(74/180) vs. 19.5% (56/287), χ2=25.69, P<0.001], systolic blood pressure [158 (141,173) mmHg vs. 152 (138,169) mmHg, Z=-2.18, P=0.029] and fasting blood glucose [6.9 (5.7,8.2) mmol/L vs. 6.3 (5.4,7.8) mmol/L, Z=-2.08, P=0.038] were higher than those in good outcome group. The metabolic phenotypes in the poor conversion group were as follows: 41 cases (22.8%) of MH-NW, 23 cases (12.8%) of MH-OW, 9 cases (5.0%) of MHO, 54 cases (30.0%) of MU-NW, 33 cases (18.3%) of MU-OW, and 20 cases (11.1%) of MUO. Conversely, the metabolic phenotypes in the good conversion group were as follows: 67 cases (23.3%) of MH-NW, 77 cases (26.8%) of MH-OW, 31 cases (10.8%) of MHO, 40 cases (13.9%) of MU-NW, 46 cases (16.0%) of MU-OW, and 26 cases (9.1%) of MUO. Regarding metabolic types, the poor conversion group comprised 73 healthy cases (40.6%) and 107 unhealthy cases (59.4%), whereas the good conversion group had 177 healthy cases (61.7%) and 110 unhealthy cases (38.3%). In terms of body mass, the poor conversion group included 94 cases (52.2%) of normal weight, 57 cases (31.7%) of overweight, and 29 cases (16.1%) of obesity. Conversely, the good conversion group had 108 cases (37.6%) of normal weight, 122 cases (42.5%) of overweight, and 57 cases (19.9%) of obesity.There were statistically significant differences in the composition ratios of physical metabolic phenotype, metabolic type, and xBMI type between the two groups of patients ( χ2=29.56, P<0.001, χ2=19.83, P<0.001, χ2=9.68, P=0.008). Multivariate Logistic regression analysis showed that after adjusting for other risk factors related to the prognosis of HICH, HDL-C ( OR=0.30, 95% CI: 0.12-0.75, P=0.010), admission GCS score ( OR=0.71, 95% CI:0.64-0.79, P<0.001), MH-OW ( OR=0.38, 95% CI: 0.17-0.82, P=0.013) and MHO ( OR=0.30, 95% CI:0.09-0.99, P=0.048) were all protective factors for adverse outcomes in patients with HICH 1 year after the onset of the disease, and hemorrhage into the ventricle ( OR=2.46, 95% CI:1.41-4.32, P=0.002) and pulmonary infection ( OR=9.13, 95% CI: 4.78- 17.44, P<0.001) were risk factors for adverse outcomes. Conclusions:MH-OW and MHO are beneficial to the prognosis of HICH patients 1 year after the onset of HICH. The secondary prevention of HICH patients should pay attention to the BMI level and comprehensive metabolic status of the patients.
8.The impact of body constitutional metabolic phenotype on the outcomes of hypertensive intracerebral hemorrhage patients one year after onset.
Yue ZHANG ; Zhiwei XU ; Yuxin LI ; Dapeng DAI ; Aimin LI
Clinical Medicine of China 2025;41(3):175-181
Objective:To explore the impact of body constitutional metabolic phenotype on the outcomes of hypertensive intracerebral hemorrhage (HICH) patients one year after onset.Methods:This study retrospectively studied the clinical data of 467 HICH patients admitted to the First People's Hospital of Lianyungang City from May 2021 to May 2023. Based on telephone follow-up after one year, the patients were categorized into two groups: a good outcome group (287 cases) and a poor outcome group (180 cases). According to the patients' body mass index (BMI) and metabolic status, the population was divided into six phenotypes: metabolically healthy with normal weight (MH-NW), metabolically healthy with overweight (MH-OW), metabolically healthy obesity (MHO), metabolically unhealthy normal weight (MU-NW), metabolically unhealthy with overweight (MU-OW), and metabolically unhealthy with obesity (MUO). The baseline data of the two groups were compared between two groups. The influencing factors of adverse outcomes in patients with HICH one year after onset were analyzed. Quantitative data that conforms to normal distribution were represented by xˉ±s, and independent sample t-test was used for comparison between two groups; The measurement data of skewed distribution was represented by M ( Q1, Q3), and Mann Whitney U test was used for comparison between the two groups; Count data was presented as an example (%), and comparison between groups was conducted using the χ2 test. Multivariate logistic regression analysis was used to analyze the influencing factors of poor prognosis in HICH patients one year after onset. Results:BMI, high density lipoprotein cholesterol(HDL-C) levels and baseline Glasgow coma score(GCS) score in the poor outcome group were lower than those in the good outcome group [23.8 (22.4, 26.1) kg/m 2 vs. 25.0 (22.5, 27.4) kg/m 2, Z=-2.31, P=0.021; 1.1 (1.0,1.4) mmol/L vs. 1.3 (1.0,1.6) mmol/L, Z=-4.18, P<0.001; 14 (13,15) score vs. 10 (7,13) score, Z=-10.20, P<0.001]. The incidence of hemorrhage into the ventricle, cerebral hernia, pulmonary infection and hydrocephalus [43.3%(78/180) vs. 23.7% (68/287). 5.6%(10/180) vs. 0.7% (2/287), 48.9%(88/180) vs. 6.6% (19/287), 5.0%(9/180) vs. 1.4% (4/287), χ2=19.86, P<0.001, χ2=10.43, P<0.001, χ2=111.90, P<0.001, χ2=5.32, P=0.021], proportion of surgical removal of hematoma [41.1%(74/180) vs. 19.5% (56/287), χ2=25.69, P<0.001], systolic blood pressure [158 (141,173) mmHg vs. 152 (138,169) mmHg, Z=-2.18, P=0.029] and fasting blood glucose [6.9 (5.7,8.2) mmol/L vs. 6.3 (5.4,7.8) mmol/L, Z=-2.08, P=0.038] were higher than those in good outcome group. The metabolic phenotypes in the poor conversion group were as follows: 41 cases (22.8%) of MH-NW, 23 cases (12.8%) of MH-OW, 9 cases (5.0%) of MHO, 54 cases (30.0%) of MU-NW, 33 cases (18.3%) of MU-OW, and 20 cases (11.1%) of MUO. Conversely, the metabolic phenotypes in the good conversion group were as follows: 67 cases (23.3%) of MH-NW, 77 cases (26.8%) of MH-OW, 31 cases (10.8%) of MHO, 40 cases (13.9%) of MU-NW, 46 cases (16.0%) of MU-OW, and 26 cases (9.1%) of MUO. Regarding metabolic types, the poor conversion group comprised 73 healthy cases (40.6%) and 107 unhealthy cases (59.4%), whereas the good conversion group had 177 healthy cases (61.7%) and 110 unhealthy cases (38.3%). In terms of body mass, the poor conversion group included 94 cases (52.2%) of normal weight, 57 cases (31.7%) of overweight, and 29 cases (16.1%) of obesity. Conversely, the good conversion group had 108 cases (37.6%) of normal weight, 122 cases (42.5%) of overweight, and 57 cases (19.9%) of obesity.There were statistically significant differences in the composition ratios of physical metabolic phenotype, metabolic type, and xBMI type between the two groups of patients ( χ2=29.56, P<0.001, χ2=19.83, P<0.001, χ2=9.68, P=0.008). Multivariate Logistic regression analysis showed that after adjusting for other risk factors related to the prognosis of HICH, HDL-C ( OR=0.30, 95% CI: 0.12-0.75, P=0.010), admission GCS score ( OR=0.71, 95% CI:0.64-0.79, P<0.001), MH-OW ( OR=0.38, 95% CI: 0.17-0.82, P=0.013) and MHO ( OR=0.30, 95% CI:0.09-0.99, P=0.048) were all protective factors for adverse outcomes in patients with HICH 1 year after the onset of the disease, and hemorrhage into the ventricle ( OR=2.46, 95% CI:1.41-4.32, P=0.002) and pulmonary infection ( OR=9.13, 95% CI: 4.78- 17.44, P<0.001) were risk factors for adverse outcomes. Conclusions:MH-OW and MHO are beneficial to the prognosis of HICH patients 1 year after the onset of HICH. The secondary prevention of HICH patients should pay attention to the BMI level and comprehensive metabolic status of the patients.
9.Changing distribution and antimicrobial resistance profiles of clinical isolates from wound pus:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Yu ZHANG ; Ying HUANG ; Yuanhong XU ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; 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 ; 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 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 2024;24(6):690-699
Objective To investigate the distribution and antimicrobial resistance profiles of the clinical isolates from wound pus in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods All the bacterial strains were isolated from wound pus samples from 2015 to 2021.The isolates were identified according to conventional methods.Antimicrobial susceptibility test was conducted by disk diffusion method or commercial automated susceptibility testing systems according to CHINET-specified uniform protocol.The results are interpreted according to the Clinical and Laboratory Standards Institute (CLSI) breakpoints (2021 Edition).Results A total of 90856 bacterial strains were isolated from wound pus samples from 2015 to 2021,of which gram positive bacteria accounted for 36.0% (32729/90856) and gram negative bacteria accounted for 64.0% (58127/90856).The most common bacterial species were Escherichia coli,Staphylococcus aureus,Klebsiella pneumoniae,Pseudomonas aeruginosa,and Enterococcus.About 88.9% of these strains were isolated from inpatients and 11.1% from outpatients.The strains collected from surgery department and internal medicine accounted for (53.4±3.6)% (49191/90856) and (9.6±1.0)% (8960/90856) on average over the 7-year period.E.coli showed low level resistance to carbapenems (1.1%).The prevalence of ESBLs-producing E.coli was 51.1%.More than 35% of the E.coli isolates were resistant to cefotaxime,ciprofloxacin,and trimethoprim-sulfamethoxazole.The prevalence of ESBLs-producing K.pneumoniae was 29.7%.The prevalence of imipenem-resistant and meropenem-resistant K.pneumoniae varied from 2015 to 2021,but reached the peak level (12.5% and 12.7%) in 2020.However,other Enterobacterales species showed low resistance rates to carbapenems.The prevalence of ESBLs-producing Klebsiella oxytoca and Proteus was 18.3% and 32.5%,respectively.About 13.1% and 10.6% of P.aeruginosa isolates were resistant to imipenem and meropenem,respectively.However,71.1% and 72.4% of A.baumannii isolates were resistant to imipenem and meropenem,respectively.The overall prevalence of MRSA was 22.7% in wound pus samples over the 7-year period.Three vancomycin-resistant strains and 122 linezolid-resistant isolates were identified in Enterococcus faecalis.Thirty-one vancomycin-resistant strains and 11 linezolid-resistant strains were detected in Enterococcus faecium.Conclusions The overall prevalence of MRSA,vancomycin-resistant Enterococcus (VRE),linezolid-resistant Enterococcus (LRE),ESBLs-producing Enterobacterales,and carbapenem-resistant organisms (CRO) in the isolates from wound pus samples was relatively lower than the corresponding prevalence in the total clinical isolates collected in the CHINET program.This finding suggests that the antimicrobial resistance profile of bacterial isolates may vary with the source of clinical samples.Therefore,we should strengthen the antimicrobial resistance surveillance for the isolates from different sites of infection.
10.Correlation between overactive bladder and allergies in children
Ningning WANG ; Aimin SUN ; Yue DU
Journal of China Medical University 2024;53(10):939-943,948
Objective To assess the clinical correlation between overactive bladder(OAB)and allergies in children.Methods The clinical characteristics of 663 children diagnosed with OAB in outpatient clinics between January 2020 and January 2022 were retro-spectively analyzed,and logistic regression was used to analyze the risk factors for OAB and evaluate the effect of antihistamine drugs on OAB.Blood and urine samples of some children with OAB were collected to analyze the expression levels of bradykinin and substance P.Results A history of eczema,urticaria,pruritus,mosquito bites,allergic rhinitis,allergic cough with asthma,food allergies,constipation,and total blood IgE levels were risk factors for OAB in children(P<0.05).The efficacy rate of antihistamine treatment in children with OAB was 95.5%,and no adverse reactions were observed,indicating that the efficacy and safety of OAB in children receiving antihista-mine treatment were good,and the proportion of children with OAB and urticaria in the antihistamine treatment group was higher(P<0.05).The total blood IgE levels in children with OAB in the effective group of antihistamine treatment were higher than those in the ineffective group(P<0.05).In addition,the expression level of bradykinin in the urine of children with OAB was significantly higher than in healthy children(P<0.05),while the level of substance P was not significantly increased(P>0.05).Conclusion OAB in chil-dren are related to their allergic status,children's previous respiratory,digestive tract,and skin allergies,and significantly elevated blood IgE levels are risk factors for OAB in children.Antihistamine treatment of OAB in children is safe and effective.OAB in children may be related to urine bradykinin.

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