1.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
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.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).
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.Epidemiological Characteristics of Esophageal Cancer Worldwide and in China,2022
Yuanjie ZHENG ; Yi TENG ; Siyi HE ; Mengdi CAO ; Qianru LI ; Nuopei TAN ; Jiachen WANG ; Tingting ZUO ; Tianyi LI ; Changfa XIA ; Wanqing CHEN
China Cancer 2025;34(3):165-170
[Purpose]To analyze the epidemiological characteristics of esophageal cancer world-wide and in China.[Methods]Data were extracted from the GLOBOCAN 2022 database.The in-cidence and mortality of esophageal cancer worldwide and in China were analyzed,stratified by sex,age group,and human development index(HDI).Spearman correlation analysis was conducted to evaluate the association between the HDI and the mortality-to-incidence ratio(MIR)of esophageal cancer.[Results]In 2022,there were an estimated 511 054 new cases and 445 391 deaths from esophageal cancer globally,with age-standardized incidence and mortality rates(ASIR and ASMR)of 5.0/105 and 4.3/105,respectively.In China,there were an estimated 224 012 new cases and 187 467 deaths accounting for 43.8%and 42.1%of global totals,respectively.Both the new cases and deaths of esophageal cancer in China ranked the first worldwide.The ASIR and ASMR in China were 8.3/105 and 6.7/105,both were as twice as the global average.The ASIR and ASMR for males were higher than those for females.The incidence and mortality of esophageal cancer increased with age,and more than 50%of global cases and deaths in individuals aged over 70 years old occurred in China.Additionally,a significantly negative correlation was ob-served between HDI and MIR of esophageal cancer(ρ=-0.67,P<0.001),and MIR in China(0.81)was comparable to that of countries or regions with a very high HDI.[Conclusion]The burden of esophageal cancer remains significant worldwide and in China,particularly among males and the elderly.The MIR of esophageal cancer in China is still relatively high.The primary and secondary prevention measures should be strengthened to reduce the incidence and mortality of esophageal cancer.
6.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
7.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.
8.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.
9.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.
10.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.

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