1.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.
2.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.
3.Expert consensus on visualized tele-round and quality control management based on the improvement of clinical practice ability
Wanhong YIN ; Xiaoting WANG ; Ran ZHOU ; Dawei LIU ; Yan KANG ; Yaoqing TANG ; Xiaochun MA ; Jianguo LI ; Zhenjie HU ; Haitao ZHANG ; Wei HE ; Lixia LIU ; Wenjin CHEN ; Ran ZHU ; Jun WU ; Hongmin ZHANG ; Lina ZHANG ; Wenzhao CHAI ; Shihong ZHU ; Wangbin XU ; Rongqing SUN ; Xiangyou YU ; Tianjiao SONG ; Ying ZHU ; Hong REN ; Ai SHANMU ; Qing ZHANG ; Wei FANG ; Xiuling SHANG ; Liwen LYU ; Shuhan CAI ; Xin DING ; Heng ZHANG ; Guang FENG ; Lipeng ZHANG ; Bo HU ; Dong ZHANG ; Weidong WU ; Feng SHEN ; Xiaojun YANG ; Zhenguo ZENG ; Qibing HUANG ; Xueying ZENG ; Tongjuan ZOU ; Milin PENG ; Yulong YAO ; Mingming CHEN ; Hui LIAN ; Jingmei WANG ; Yong LI ; Feng QU ; Gang YE ; Rongli YANG ; Xiukai CHEN ; Suwei LI ; Juxiang WANG ; Yangong CHAO
Chinese Journal of Internal Medicine 2025;64(2):101-109
Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.
4.The influence of diabetes mellitus and high-sensitivity C-reactive protein on the risk of diges-tive system malignancy: a prospective cohort study
Kuan LIU ; Jiaxing LI ; Chao MA ; Wanchao WANG ; Yuan TIAN ; Zhigang DONG ; Wenqiang WEI ; Shuohua CHEN ; Shouling WU ; Siqing LIU
Chinese Journal of Digestive Surgery 2025;24(1):93-102
Objective:To investigate the influence of diabetes mellitus (DM) and high-sen-sitivity C-reactive protein (Hs-CRP) on the risk of digestive system malignancy.Methods:The pro-spective cohort study was conducted. The clinical data of 93 928 participants who participated health examination in 9 hospitals at Tangshan, including Kailuan General Hospital Affiliated to North China University of Science and Technology et al, in 2006 were selected. According to the presence or absence of DM and the level of Hs-CRP, all participants were divided into 4 groups, including the DM(-)CRP(-) group defined as absence of DM and Hs-CRP ≤3 mg/L, the DM(-)CRP(+) group defined as absence of DM and Hs-CRP>3 mg/L, the DM(+)CRP(-) group defined as presence of DM and Hs-CRP ≤3 mg/L, and the DM(+)CRP(+) group defined as presence of DM and Hs-CRP >3 mg/L. The data of participants were collected by a fixed team of physicians. The first physical examination in 2006 was taken as the starting point for follow-up. The end event of follow-up was defined as the occurrence of digestive system malignancy or death, and the follow-up was up to December 31, 2021. Observation indicators: (1) comparison of clinical data among the 4 groups of participants; (2) the incidence and cumulative incidence rate of digestive system malignancy in participants; (3) influence of DM and Hs-CRP level on the risk of digestive system malignancy; (4) the combined influence of DM and Hs-CRP level on the risk of digestive system malignancy; (5) sensitivity analysis. Comparison of measurement data with normal distribution among multiple groups was conducted using the one-way analysis of variance. For pairwise comparison, least significant difference test was used for homogeneity of variance, and Dunnett′s T3 test was used for heterogeneity of variance. Comparison of measurement data with skewed distribution among multiple groups was conducted using the Kruskal-Wallis rank sum test, and Dunn-Bonferroni test was used for pairwise comparison. Comparison of count data among multiple groups was conducted using the chi-square test, and Bonferroni test was used among multiple comparisons. The Kaplan-Meier method was used to plot cumulative incidence curve, and Log-rank test was used for cumulative incidence rate analysis. The Cox proportional risk model was used for multivariate analysis. All models were adjusted for relevant confounders. Results:(1) Comparison of clinical data among the 4 groups of participants. Of the 93 928 participants, there were 70 743 cases in the DM(-)CRP(-) group, 14 644 cases in the DM(-)CRP(+) group, 6 425 cases in the DM(+)CRP(-) group, and 2 116 cases in the DM(+)CRP(+) group. There were significant differences in gender, age, fasting blood glucose, Hs-CRP, triglyceride, alanine aminotransferase, body mass index, marrital status, smoking, drinking, high school degree or above, physical exercise, high salt diet, high fat diet, positive hepatitis B virus surface antigen, fatty liver, liver cirrhosis, gallstone, taking hypoglycemic drugs, taking lipid-lowering drugs among the 4 groups of participants ( P<0.05). (2) The incidence and cumulative incidence rate of digestive system malignancy in participants. At the end-up of follow-up, 2 008 cases developed digestive system malignancy in the 93 928 participants, including 717 cases of colorectal cancer, 456 cases of liver cancer, 396 cases of gastric cancer, 195 cases of esophageal cancer, 144 cases of pancreatic cancer, 65 cases of gallbladder cancer or extrahepatic cholangiocarcinoma, 35 cases of small bowel cancer. The cumulative incidence rates of digestive system malignancy were 2.19%, 2.42%, 2.86%, 3.59% in participants of the DM(-)CRP(-) group, DM(-)CRP(+) group, DM(+)CRP(-) group, DM(+)CRP(+) group, respectively, showing a significant difference among the 4 groups ( χ2=31.72, P<0.05). (3) Influence of DM and Hs-CRP level on the risk of digestive system malignancy. After adjusting for the confounding factors of the participants, results of multivariate analysis showed that DM and Hs-CRP >3 mg/L were independent influencing factors for the incidence of digestive system malignancy ( hazard ratio=1.32, 1.19, 95% confidence interval as 1.13-1.56, 1.06-1.33, P<0.05). Futher analysis showed that there was a significant difference in interaction between DM and Hs-CRP >3 mg/L ( P<0.05). (4) The combined influence of DM and Hs-CRP level on the risk of digestive system malign-ancy. After adjusting for confounding factors, results of multivariate analysis showed that using the DM(-)CRP(-) group as the control group, the risk of incidence of digestive system malignancy increased in the DM(-)CRP(+) group, DM(+)CRP(-) group, and DM(+)CRP(+) group, respectively ( hazard ratio=1.14, 1.23, 1.79, 95% confidence interval as 1.01-1.29, 1.02-1.48, 1.38-2.31, P<0.05). In the site-specific analysis of digestive system malignancy, using the DM(-)CRP(-) group as the control group, the risk of incidence of liver cancer increased in the DM(-)CRP(+) group ( hazard ratio=1.37, 95% confidence interval as 1.07-1.75, P<0.05), the risk of incidence of liver cancer and pancrea-tic cancer increased in the DM(+)CRP(-) group ( hazard ratio=1.60, 1.74, 95% confidence interval as 1.16-2.21, 1.00-3.02, P<0.05), the risk of incidence of small bowel cancer, pancreatic cancer and colorectal cancer increased in the DM(+)CRP(+) group ( hazard ratio=5.05, 2.31, 2.23, 95% confidence interval as 1.57-16.21, 1.00-5.31, 1.54-3.24, P<0.05). (5) Sensitivity analysis. After adjusting for confounding factors of excluding 3 types of participants (103 cases of digestive system malignancy within 1 year of follow-up, 2 370 cases of taking glucose-lowering drugs, and 915 cases of taking lipid-lowering drugs), results of multivariate analysis showed that using the DM(-)CRP(-) group as the control group, the risk of incidence of digestive system malignancy increased in the DM(+)CRP(-) group, and DM(+)CRP(+) group, respectively ( hazard ratioexcluding cases of digestive system malignancy within 1 year of follow-up=1.26, 1.66, 95% confidence interval as 1.04-1.52, 1.26-2.18, P<0.05; hazard ratioexcluding cases taking glucose-lowering drugs=1.23, 1.75, 95% confidence interval as 1.02-1.49, 1.31-2.33, P<0.05; hazard ratioexcluding cases taking lipid-lowering drugs=1.24, 1.80, 95% confidence interval as 1.03-1.49, 1.39-2.34, P<0.05). Conclusions:DM and Hs-CRP >3 mg/L are independent influencing factors for the incidence of digestive system malignancy. There is an interation and synergistic effect between DM and Hs-CRP to promote the incidence of digestive system malignancy.
5.A practice guideline for therapeutic drug monitoring of mycophenolic acid for solid organ transplants.
Shuang LIU ; Hongsheng CHEN ; Zaiwei SONG ; Qi GUO ; Xianglin ZHANG ; Bingyi SHI ; Suodi ZHAI ; Lingli ZHANG ; Liyan MIAO ; Liyan CUI ; Xiao CHEN ; Yalin DONG ; Weihong GE ; Xiaofei HOU ; Ling JIANG ; Long LIU ; Lihong LIU ; Maobai LIU ; Tao LIN ; Xiaoyang LU ; Lulin MA ; Changxi WANG ; Jianyong WU ; Wei WANG ; Zhuo WANG ; Ting XU ; Wujun XUE ; Bikui ZHANG ; Guanren ZHAO ; Jun ZHANG ; Limei ZHAO ; Qingchun ZHAO ; Xiaojian ZHANG ; Yi ZHANG ; Yu ZHANG ; Rongsheng ZHAO
Journal of Zhejiang University. Science. B 2025;26(9):897-914
Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C0), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug-drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage*
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Drug Monitoring/methods*
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Humans
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Organ Transplantation
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Immunosuppressive Agents/administration & dosage*
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Delphi Technique
6.Clinical efficacy of lateral interbody fusion versus posterior lumbar interbody fusion in the treatment of severe lumbar spinal stenosis
Bing CHEN ; Chao CHEN ; Xiaopeng LI ; Hanming BIAN ; Wentao WAN ; Gang LIU ; Dong ZHAO ; Haiyun YANG ; Limin SUN ; Baoshan XU ; Xiangqian FANG ; Xinlong MA ; Qiang YANG
Chinese Journal of Orthopaedics 2025;45(9):596-603
Objective:To investigate the clinical efficacy of lumbar lateral interbody fusion (LLIF) versus posterior lumbar interbody fusion (PLIF) in the treatment of severe lumbar spinal stenosis.Methods:The data of patients with severe lumbar spinal stenosis who underwent LLIF or PLIF from February 2019 to December 2023 were retrospectively analyzed. There were 30 patients in the LLIF group, 10 males and 20 females, aged 62.7±5.6 years (range, 53-74 years), including 21 cases of single segment and 9 cases of double segment. There were 46 patients in the PLIF group, including 20 males and 26 females, aged 63.2±8.4 years (range, 43-75 years), 40 cases of single segment and 6 cases of double segment. The visual analogue scale (VAS), Oswestry disability index (ODI), intervertebral space height, intervertebral foramen height and postoperative complications were compared between the two groups.Results:All patients were followed up for an average of 21.3±6.4 months (range, 12-32 months). The intraoperative blood loss in the LLIF group was 112.2±76.9 ml, which was significantly lower than 193.9±88.2 ml in the PLIF group ( P<0.05). The VAS scores of back pain and leg pain after operation were significantly lower than those before operation in the two groups ( P<0.05). There was no statistically significant difference between groups in back pain VAS scores at preoperative, 6 months postoperative, and final follow-up ( P>0.05); the back pain VAS score at 1 month postoperatively in the LLIF group was 1.6±1.2, which was less than 2.8±0.7 in the PLIF group ( P<0.05). There was no statistically significant difference between groups in leg pain VAS scores at preoperative, 1 month postoperative, and 6 months postoperative ( P>0.05); the leg pain VAS score at the final follow-up in the LLIF group was 1.2±1.5, which was smaller than 1.8±1.0 in the PLIF group ( P<0.05). The postoperative ODI was smaller than the preoperative one in both groups, and the difference was statistically significant ( P<0.05); the preoperative, 1-month postoperative, 6-month postoperative, and final follow-up ODIs in the LLIF group were 45.7%±16.0%, 17.9%±12.0%, 16.2%±11.6%, and 15.7%±11.7%, and those in the PLIF group were 47.9%±15.4%, 20.1%±9.3%, 16.9%±10.6%, and 14.6%±11.0% in the PLIF group, and the difference between the groups was not statistically significant ( P>0.05). The preoperative intervertebral space height in the LLIF group was 10.6±2.0 mm, which was smaller than that in the PLIF group 11.8±2.2 mm ( P<0.05). The intervertebral space heights in the immediate postoperative period and at the final follow-up were 13.3±2.3 mm and 12.3±2.2 mm in the LLIF group and 13.7±1.7 mm and 13.0±1.9 mm in the PLIF group ( P>0.05). The preoperative intervertebral foraminal height in the LLIF group was 18.0±3.2 mm, which was smaller than that of 19.7±2.4 mm in the PLIF group ( P<0.05); the intervertebral foraminal heights in the immediate postoperative period and at the final follow-up were 21.4±2.5 mm and 20.2±2.4 mm in the LLIF group, and in the PLIF group were 20.7±2.4 mm and 19.7±2.6 mm in the PLIF group ( P>0.05). In the LLIF group, 2 cases had femoral nerve injury and 2 cases had transient back pain after operation. There were 2 cases of cerebrospinal fluid leakage, 1 case of screw loosening, and 2 cases of deep vein thrombosis in the PLIF group. In the PLIF group, 2 patients underwent revision, including 1 case due to cage displacement and 1 case due to screw malposition. The fusion settling rate was 21% (8/39) in the LLIF group and 12% (6/52) in the PLIF group ( P>0.05). Conclusion:Both LLIF and PLIF can effectively restore the intervertebral height, improve the lumbar function and the symptoms of back and leg pain in the treatment of severe lumbar spinal stenosis.
7.Administrative burden among primary healthcare professionals and its impact mechanism on job burnout:An exploratory sequential mixed-methods study
Shi-chao ZHAO ; Ming-ze XIN ; Zi-qian TANG ; Ya-fang DONG ; He-xi LI ; Hui-fen MA ; Tao WANG
Chinese Journal of Health Policy 2025;18(9):31-38
Objective:To examine the manifestations and causes of administrative burden among primary healthcare professionals,and to explore its impact on job burnout through the mediating role of role conflict,providing theoretical and empirical support for governance-level burden-reduction strategies.Methods:An exploratory sequential mixed-methods design was employed,focusing on primary healthcare professionals in Shandong Province.In the first phase,in-depth interviews were conducted with 175 participants;in the second phase,a questionnaire survey of 1,096 participants and follow-up interviews with 107 participants were carried out.Results:The proportions of respondents who reported"heavy"or"very heavy"burdens were 62.7%for inspection,54.8%for documentation,51.8%for reporting,and 24.4%for meetings.Structural equation modeling showed that administrative burden had a direct effect on job burnout(0.150)and an indirect effect through role conflict(0.093).Qualitative findings further indicated that administrative burden largely stemmed from public health traceability requirements and medical insurance policies,and operated through both resource-based and value-based conflicts.Conclusions:Primary healthcare professionals face considerable administrative burdens,which may heighten job burnout through role conflict.Governance reforms should optimize inspection and assessment,streamline data reporting,refine record-keeping,and promote collaborative governance to break the chain of institutional pressure leading to burnout.
8.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.
9.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.
10.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.

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