1.Prognostic study of neoadjuvant therapy for pancreatic cancer based on propensity score matching and subgroup analysis
Xiaohao ZHENG ; Jingyu ZHANG ; Xiaojie CHEN ; Zhen HAO ; Jing LIU ; Zewen ZHANG ; Wanqing YU ; Yun YANG
International Journal of Surgery 2025;52(4):230-238
Objective:To investigate whether neoadjuvant therapy can improve the prognosis of patients with pancreatic cancer.Methods:A retrospective case-control study analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database on 12, 103 patients who underwent surgical treatment between January 1, 2010, and December 31, 2021. Patients were divided into the neoadjuvant therapy group ( n=3 276) and the upfront surgery group ( n=8 827) based on whether they received neoadjuvant treatment. The neoadjuvant therapy group included 2 342 patients receiving neoadjuvant chemotherapy and 934 patients receiving neoadjuvant chemoradiotherapy. The upfront surgery group consisted of 4 335 patients receiving adjuvant chemotherapy, 1 987 patients receiving adjuvant chemoradiotherapy, 63 patients receiving adjuvant radiotherapy, and 2 442 patients undergoing surgery alone. Propensity score matching was used to eliminate group differences and create a cohort with no statistical differences in other clinicopathological features except for the grouping variable. Variables such as age, gender, tumor location, race, population of residence, tumor diameter, household income, TNM stage, and information on radiotherapy and chemotherapy were used for 1∶1 case matching. T stage, N stage, and the use of radiotherapy or chemotherapy were matched exactly. After matching, 1 182 patients were included in each group: the neoadjuvant therapy group contained 1 155 patients receiving neoadjuvant chemoradiotherapy and 27 receiving neoadjuvant chemotherapy, while the upfront surgery group comprised 848 patients receiving adjuvant chemotherapy and 334 receiving adjuvant chemoradiotherapy. TNM staging was reported according to the 7th edition of the AJCC guidelines. The primary outcome was overall survival. Measurement data with skewed distributions were expressed as M( Q1, Q3), and intergroup comparisons were conducted using the Wilcoxon rank-sum test. Categorical data were compared using the chi-square test or the Fisher′s exact test. The Log-rank test and subgroup analyses to assess interactions between neoadjuvant therapy and subgroup in COX regression models were used to compare survival benefits across variables. Landmark analysis was performed to create segmented survival curves, studying the impact of neoadjuvant therapy on prognosis during different follow-up periods. Results:The neoadjuvant therapy group had a higher proportion of T 4 tumor involving celiac axis, superior mesenteric artery, and/or common hepatic artery compared to the upfront surgery group (14.7% vs 2.8%, P<0.001). Additionally, significant differences were observed between groups in terms of race, location, population of residence, age, tumor diameter, tumor stage, and adjuvant therapy regimen ( P<0.05). The median overall survival time in the neoadjuvant therapy group was 30 months, compared to 22 months in the upfront surgery group ( P<0.001). In the neoadjuvant therapy group, the median survival was 30 months for both neoadjuvant chemotherapy and chemoradiotherapy patients; in the upfront surgery group, it was 26 months for both adjuvant chemotherapy and chemoradiotherapy patients, 17 months for adjuvant radiotherapy patients, and 12 months for surgery-only patients. After propensity score matching, there were no differences in the distribution of clinical characteristics between groups ( P>0.05), and all patients in the matched cohort had received chemotherapy. The matched neoadjuvant therapy group had a longer median overall survival compared to the upfront surgery group (30 months vs 27 months, P<0.001). Subgroup interaction analysis revealed that T stage had a significant interaction with neoadjuvant therapy, both before (T 4 stage: HR=0.382, 95% CI: 0.319-0.458; T 2-T 3 stages: HR=0.696, 95% CI: 0.656-0.738; T 1 stage: HR=1.199, 95% CI: 0.867-1.657; interaction P<0.001) and after matching (T 4 stage: HR=0.581, 95% CI: 0.414-0.814; T 2-T 3 stages: HR=0.827, 95% CI: 0.734-0.931; T 1 stage: HR=1.320, 95% CI: 0.716-2.433; interaction P=0.043). Subgroup interaction analysis indicated that T 1 patients did not benefit from neoadjuvant therapy; survival curves plotted for matched T 1 patients showed no difference in survival between the neoadjuvant therapy group and the upfront surgery group ( P=0.323). Conversely, non-T 1 (T 2-T 4) stage patients showed significant survival benefits in both unmatched and matched cohorts ( P<0.001). Landmark analysis showing that the survival benefits occurred mainly in the early postoperative period of up to 3 years ( P<0.001), but there was no difference in overall survival between the neoadjuvant therapy group and the upfront surgery group of >3 years ( P>0.05). Patients with Arterial invasion (T 4 stage compared to T 1-T 3 stages) showed a similarly significant interaction with the benefit of neoadjuvant therapy in both the pre-matching cohort (interaction P<0.001) and the post-matching cohort (interaction P=0.037). Patients with T 4 stage disease in the neoadjuvant therapy group had longer overall survival compared to the upfront surgery group (median overall survival in pre-matching cohort: 30 months vs 13 months, P<0.001; median overall survival in post-matching cohort: 28 months vs 18 months, P=0.001). Among T 4 stage patients in the post-matching cohort, neoadjuvant therapy provided significant survival benefits during the early postoperative period of up to 3 years ( P=0.001). However, there was no difference in overall survival between the neoadjuvant therapy group and the direct surgery group beyond 3 years( P=0.729). Conclusions:The prognosis in the neoadjuvant therapy group was better than in the upfront surgery group. Propensity score matching and subgroup interaction analysis showed that non-T 1 and T 4 stage patients benefited more from neoadjuvant therapy, with benefits mainly seen in the early postoperative period (≤3 years).
2.Mechanism of Huazhuo Jiedu Prescription in Alleviating Renal Fibrosis in 5/6 Nephrectomy Rats Based on AMPK/mTOR Pathway
Wanqing WANG ; Yashi WANG ; Hui GAO ; Linlin ZHENG ; Dong BIAN ; Cun FENG ; Xiaona WEI
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(22):90-97
ObjectiveBased on the AMP-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR) signaling pathway, this study aimed to observe the effect of the Huazhuo Jiedu prescription on renal fibrosis in 5/6 nephrectomy rats and explore its underlying mechanism. MethodsA total of 67 SPF-grade male SD rats were used, of which 11 were randomly selected as the normal group. A chronic renal failure (CRF) model was established using 5/6 nephrectomy. The successfully modeled rats were randomly assigned to the model group, losartan potassium group (4.5 mg·kg-1), and low- (1.175 g·kg-1), medium- (2.35 g·kg-1) and high-dose (4.7 g·kg-1) Huazhuo Jiedu prescription groups, with 9 rats per group. Each group received an equivalent volume of saline or the corresponding concentration of Huazhuo Jiedu prescription by gavage once daily for 8 weeks. Hematoxylin-eosin (HE) and Masson staining were used to observe renal tissue pathological changes. Transmission electron microscopy examined renal ultrastructure. Immunohistochemistry (IHC) detected expressions of α-smooth muscle actin (α-SMA) and transforming growth factor-β1 (TGF-β1). Western blot analyzed expression levels of microtubule-associated protein Ⅰ light chain 3Ⅱ (LC3Ⅱ), Beclin1, p62, AMPK, phosphorylated AMPK (p-AMPK), mTOR, and phosphorylated mTOR (p-mTOR). ResultsCompared with the normal group, the model group exhibited glomerular shrinkage, mesangial and interstitial thickening, and tubular vacuolar degeneration, with no evident autophagosomes or autophagolysosome structures. Expression levels of α-SMA and TGF-β1 were significantly increased (P0.01), while p-AMPK/AMPK, Beclin1, and LC3Ⅱ were significantly decreased (P0.01), and p-mTOR/mTOR and p62 were significantly increased (P0.01). Compared with the model group, the medium- and high-dose Huazhuo Jiedu prescription groups and the losartan potassium group showed varying degrees of pathological improvement. Autophagosomes with double- or multiple-layer membranes and autophagolysosomes with monolayer membranes containing undegraded organelles were observed. Renal α-SMA and TGF-β1 protein expression levels were markedly reduced (P0.05, P0.01), p-mTOR/mTOR and p62 were significantly decreased (P0.05, P0.01), and p-AMPK/AMPK, Beclin1, and LC3Ⅱ expression levels were significantly increased (P0.05, P0.01). ConclusionHuazhuo Jiedu prescription may improve renal fibrosis in 5/6 nephrectomy rats by regulating the AMPK/mTOR signaling pathway and enhancing autophagy.
3.Corrigendum: Comparative analysis of cancer statistics in China and the United States in 2024.
Yujie WU ; Siyi HE ; Mengdi CAO ; Yi TENG ; Qianru LI ; Nuopei TAN ; Jiachen WANG ; Tingting ZUO ; Tianyi LI ; Yuanjie ZHENG ; Changfa XIA ; Wanqing CHEN
Chinese Medical Journal 2025;138(10):1260-1260
4.Trends and Decompostion of Disease Burden for Lung Cancer Worldwide and in China from 1990 to 2021
Tianyi LI ; Yuanjie ZHENG ; Yi TENG ; Qianru LI ; Tingting ZUO ; Nuopei TAN ; Jiachen WANG ; Siyi HE ; Mengdi CAO ; Changfa XIA ; Wanqing CHEN
China Cancer 2025;34(5):355-367
[Purpose]To analyze the trends of disease burden for lung cancer worldwide and in China from 1990 to 2021.[Methods]Data of the disease burden of lung cancer and population demographics in 1990 and 2021 stratified by sex and age groups for global,five SDI quintiles re-gions,and eight countries including China,Japan,Republic of Korea,United Kingdom,France,United States,Canada,and Australia were extracted from the Global Burden of Disease Study 2021(GBD 2021)database.The age-standardized mortality rate(ASMR)and age-standard-ized disability-adjusted life year rate(ASDR)of lung cancer attributable to 7 level-3 risk factors in China for 1990 and 2021 were also extracted.Counterfactual analysis was used to decompose changes in lung cancer deaths and DALY from 1990 to 2021 into four contributing factors:popu-lation size,population structure,age-standardized incidence or prevalence,and lung cancer case fatality or disease severity.The percentage changes in lung cancer deaths and DALY attributed to these four factors were calculated respectively.[Results]In 2021,there were 934 704 new cases and 814 364 deaths of lung cancer in China.From 1990 to 2021,the incidence,preva-lence,mortality,and DALY rates of lung cancer in China increased faster than those worldwide and in high-middle SDI regions,which was similar to Japan and Republic of Korea.In contrast,the mortality rates of lung cancer decreased in United States and United Kingdom;and the DALY rates of lung cancer decreased in United States,United Kingdom,Canada and Australia.From 1990 to 2021,the age-related lung cancer deaths and DALY in China increased by 193.91%and 146.20%,respectively.The primary contributor to the increase in lung cancer deaths was population aging(102.82%)among men and rising age-standardized incidence(119.00%)among women,while the primary contributor to the increase in DALY was rising age-standardized prevalence for both men(153.12%)and women(218.77%).In 2021,the top three risk factors contributing to lung cancer ASMR and ASDR in China were smoking,particulate matter pollution and occupational carcinogen exposure.Compared with 1990,the ASMR of lung cancer and its proportion at-tributable to particulate matter pollution and low dietary fruits were decreased,while the propor-tions in ASDR of lung cancer attributable to smoking and secondhand smoke increased.[Conclu-sion]Lung cancer is a major public health challenge in China.Compared with worldwide,high-middle SDI regions and certain developed countries,China has experienced faster growth in the incidence,prevalence,mortality and DALY of lung cancer,especially among women.To reduce disease burden,sustained efforts on lung cancer prevention and control are urgently required in China.
5.Changing resistance profiles of Haemophilus influenzae and Moraxella catarrhalis isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Hui FAN ; Chunhong SHAO ; Jia WANG ; Yang YANG ; Fupin HU ; Demei ZHU ; Yunsheng CHEN ; Qing MENG ; Hong ZHANG ; Chun WANG ; Fang DONG ; Wenqi SONG ; Kaizhen WEN ; Yirong ZHANG ; Chuanqing WANG ; Pan FU ; Chao ZHUO ; Danhong SU ; Jiangwei KE ; Shuping ZHOU ; Hua ZHANG ; Fangfang HU ; Mei KANG ; Chao HE ; Hua YU ; Xiangning HUANG ; Yingchun XU ; Xiaojiang ZHANG ; Wenen LIU ; Yanming LI ; Lei ZHU ; Jinhua MENG ; Shifu WANG ; Bin SHAN ; Yan DU ; Wei JIA ; Gang LI ; Jiao FENG ; Ping GONG ; Miao SONG ; Lianhua WEI ; Xin WANG ; Ruizhong WANG ; Hua FANG ; Sufang GUO ; Yanyan WANG ; Dawen GUO ; Jinying ZHAO ; Lixia ZHANG ; Juan MA ; Han SHEN ; Wanqing ZHOU ; Ruyi GUO ; Yan ZHU ; Jinsong WU ; Yuemei LU ; Yuxing NI ; Jingrong SUN ; Xiaobo MA ; Yanqing ZHENG ; Yunsong YU ; Jie LIN ; Ziyong SUN ; Zhongju CHEN ; Zhidong HU ; Jin LI ; Fengbo ZHANG ; Ping JI ; Yunjian HU ; Xiaoman AI ; Jinju DUAN ; Jianbang KANG ; Xuefei HU ; Xuesong XU ; Chao YAN ; Yi LI ; Shanmei WANG ; Hongqin GU ; Yuanhong XU ; Ying HUANG ; Yunzhuo CHU ; Sufei TIAN ; Jihong LI ; Bixia YU ; Cunshan KOU ; Jilu SHEN ; Wenhui HUANG ; Xiuli YANG ; Likang ZHU ; Lin JIANG ; Wen HE ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):30-38
Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91%of the total clinical isolates and 4.07%of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89%were isolated from children and 33.11%were isolated from adults.More than 90%of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79%in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06%were isolated from children and 19.94%isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0%.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.
6.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.
7.Surveillance of antimicrobial resistance in clinical isolates of Escherichia coli:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shanmei WANG ; Bing MA ; Yi LI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Zhaoxia ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Aimin WANG ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WEN ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(1):39-47
Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)%.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0%vs 29.5%).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7%vs 7.8%,0.8%vs 0.1%,both P<0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)%with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9%and 1.8%,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1%).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10%.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P<0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.
8.Analysis for diagnostic value of laboratory indicators inGuillain-Barre syndrome
Xuewen ZHENG ; Shilan XU ; Guoye LIU ; Wanqing ZHOU
Chinese Journal of Clinical Laboratory Science 2025;43(2):102-105
Objective To explore the diagnostic value of the phenomenon of protein-cell separation in cerebrospinal fluid(CSF),as well as the single and combined detections of CSF immunoglobulin G(CSF-IgG),CSF albumin(CSF-ALB)and serum immunoglobu-lin G(S-IgG)for Guillain-Barre syndrome(GBS).Methods A retrospective analysis was conducted on the clinical data of 65 GBS patients(GBS group)and 65 patients with other neurological diseases(non-GBS group).CSF and serum samples were collected from both the groups to analyze the diagnostic efficacy of protein-cell separation phenomenon in CSF,as well as the single and combined de-tections of CSF-IgG,CSF-ALB,and serum-IgG(S-IgG)in GBS.Results CSF protein-cell separation phenomenon was observed in 60.00%(39/65)of GBS patients.Prodromal events were presented in 67.69%(44/65)of GBS patients,which mainly were upper re-spiratory tract infection(43.08%,28/65),digestive tract infection(9.23%,6/65),and herpetic virus infection(7.69%,5/65).The levels of CSF-IgG,CSF-ALB,and S-IgG in the GBS group were significantly higher than those in non-GBS group(P<0.05).The areas under the ROC curves(AUCROC)for single CSF-IgG,CSF-ALB,S-IgG,protein-cell separation phenomenon IN CSF,and the combination of all the four parameters in diagnosis of GBS were 0.754,0.705,0.682,0.708,and 0.840,respectively.The diagnostic specificities were 87.7%,75.4%,87.7%,81.5%,and 96.9%,respectively.Conclusion Most of the GBS patients were found to have CSF protein-cell separation phenomenon and history of prodromal infection.CSF-IgG,CSF-ALB,S-IgG,and CSF protein-cell separation phenomenon exhibited independent diagnostic value for GBS.The combined detection of the four indicators could improve the diagnostic efficacy for GBS.
9.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
10.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

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