1.Retraction Note: Fluoxetine is Neuroprotective in Early Brain Injury via its Anti-inflammatory and Anti-apoptotic Effects in a Rat Experimental Subarachnoid Hemorrhage Model.
Hui-Min HU ; Bin LI ; Xiao-Dong WANG ; Yun-Shan GUO ; Hua HUI ; Hai-Ping ZHANG ; Biao WANG ; Da-Geng HUANG ; Ding-Jun HAO
Neuroscience Bulletin 2025;41(11):2106-2106
3.Teaching practice of movable virtual reality equipment in human anatomy classroom teaching
Ping LIU ; Xuan FANG ; Hui-Ru DING ; Li-Ju LUAN ; Yan ZHANG ; Jun WANG ; Huai-Cun LIU ; Wei-Guang ZHANG
Acta Anatomica Sinica 2025;56(5):607-611
Objective To explore the integration value of mobile virtual reality devices in the classroom teaching of human anatomy,and to evaluate their potential impact on the in-depth construction of human anatomy knowledge,the cultivation of spatial cognitive ability,and the transformation of teaching paradigms from the perspectives of cognitive load theory and situated learning.Methods The undergraduate students majoring in clinical medicine in Peking University were selected as the research objects.Among them,students in grade 2019 were the control group,and students in grade 2022 were the experimental group,introducing movable virtual anatomy equipment and other teaching auxiliary method in theory and practice courses.The final exam scores of the two groups of students were compared,and a questionnaire survey was conducted for the experimental group after the course,and the survey result were statistically analyzed.Results The final examination result showed that the average score of the experimental group was 82.47±10.19,and the average score of the control group was 74.82±16.56,which was significantly higher in the experimental group than in the control group,with statistical significance(P<0.05).The questionnaire survey result showed that compared with traditional classroom teaching,94.62%of students preferred the new auxiliary teaching mode such as VR,96.77%of students believed that VR assisted teaching could achieve the traditional teaching effect or better,95.7%of them think that it improved students' interest in learning human anatomy,and 98.92%thought that it improved students' knowledge of anatomy.Conclusion The application of mobile virtual reality devices in anatomy classroom teaching provides immersive and interactive 3D visualization teaching scenarios,effectively reducing students' cognitive load on abstract and complex anatomical structures,promoting spatial understanding and knowledge internalization,significantly improving teaching effectiveness and self-learning ability,thus changing the traditional anatomy teaching mode and laying a solid foundation for the development of future medical education and the cultivation of medical talents.
4.Construction of a machine learning model based on the Ki67 positive index to predict the recurrence risk of hepatocellular carcinoma
Haoran LI ; Yan YU ; Fangying FAN ; Wenzhen DING ; Hui FENG ; Minghua YING ; Jiawei LI ; Qingqing SUN ; Lele BIAN ; Haokai XU ; Zhanyue CHEN ; Jie YU ; Ping LIANG
Chinese Journal of Hepatology 2025;33(9):898-909
Objective:To screen the optimal machine learning model for predicting the recurrence condition of hepatocellular carcinoma (HCC) at different time points post-surgery, based on the cutoff value of the Ki67 positive proliferation index condition calculated from recurrence-free survival and combined with various clinical features.Methods:retrospective study included initially treated patients with solitary HCC who underwent radical surgery at the Fifth Medical Center of the PLA General Hospital from January 2013 to March 2023. Data included general clinical data, preoperative laboratory parameters, and surgical pathology information about the subjects. The postoperative recurrence status was assessed by querying the medical record system or by telephone follow-up. The Ki67 positive index cutoff value was determined by the X-tile software based on the patient's recurrence-free survival status and time analysis. Survival rates were calculated using the Kaplan-Meier method, and survival curves were plotted. The study population was randomly divided into training and testing groups in a 7:3 ratio using a computer-generated random number method. The minimum redundancy maximum relevance (mRMR) method was used for feature variable selection. Predictive models for postoperative HCC recurrence conditions in patients with HCC were constructed using random forest, support vector machine, logistic regression, and gradient boosting decision tree machine learning algorithms. Inter-group comparisons for continuous data were performed using the t-test or Mann-Whitney U test. Inter-group comparisons of enumeration data were performed using the Pearson χ2 test, continuity-corrected χ2 test, or Fisher's exact test. Results:The cutoff values for the Ki67 positivity index were 0.3 and 0.5 in 510 cases, with a follow-up time ranging from 1.2 to 11.4 years (median: 6.2 years). The recurrence-free survival time was between 1 and 135 months (median: 32 months), with recurrence-free survival rates post-surgery at 1, 2, 3, and 5 years were 87.5%, 77.1%, 61.2%, and 54.5%, respectively. The top five variables predicted HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years, in accordance with information obtained by the mRMR screen out. The Ki67 positivity index screened a successfully constructed machine learning model to predict HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years. The machine learning model based on the gradient boosting decision tree algorithm had the best prediction performance among them (areas under the receiver operating characteristic curves for predicting HCC recurrence within six months in the training and validation sets were 0.996 and 0.946, and accuracies were 0.972 and 0.935, respectively).Conclusion:A machine learning model was successfully constructed using the Ki67 positivity index combined with four readily available clinical features to predict HCC recurrence. The machine learning model based on the gradient boosting decision tree algorithm demonstrated the best performance in terms of predicting HCC recurrence within six months after surgery.
5.National bloodstream infection bacterial resistance surveillance report 2023: Gram-positive bacteria
Chaoqun YING ; Jinru JI ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(2):118-132
Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System(BRICS)during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute(CLSI). Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus( n=1 544,35.2%),coagulase-negative Staphylococci( n=1 441,32.9%), Enterococcus faecium( n=574,13.1%), Enterococcus faecalis( n=385,8.8%),and α-hemolytic Streptococci( n=187,4.3%). The prevalence of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)was 26.2%(405/1 544)and 69.8%(1 006/1 441),respectively. Notably,all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility(>97.0%)to cephalobiol,rifampicin,trimethoprim-sulfamethoxazole,linezolid,minocycline,tigecycline,and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium(resistance to vancomycin and teicoplanin:both 1.7%)compared to Enterococcus faecalis(both 0.3%). The detection rates of MRSA and MRCNS exhibited significant regional variations across the country( χ2=17.674 and 148.650,respectively,both P<0.001). No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA( χ2=14.111, P<0.001)and MRCNS( χ2=4.828, P=0.028)in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA( χ2=18.986, P<0.001)and MRCNS( χ2=4.477, P=0.034)in less developed regions(per capita GDP
6.National bloodstream infection bacterial resistance surveillance report (2023) : Gram-negative bacteria
Jinru JI ; Zhiying LIU ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(1):47-62
Objective:To report the results of bacterial resistant investigation collaborative system(BRICS)on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023,and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 were used to analyze the data.Results:During the study period,11 492 strains of Gram-negative bacteria were collected from 60 hospitals,of which 10 098(87.9%)were Enterobacterales and 1 394(12.1%)were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli(50.0%), Klebsiella pneumoniae(26.1%), Pseudomonas aeruginosa(5.1%), Acinetobacter baumannii complex(5.0%)and Enterobacter cloacae complex(4.1%). The ESBL-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus mirablilis were 46.8%(2 685/5 741),18.3%(549/2 999)and 44.0%(77/175),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(76/5 741)and 15.0%(450/2 999);32.9%(25/76)and 78.0%(351/450)of CREC and CRKP were sensitive to ceftazidime/avibactam combination,respectively. 94.7%(72/76)and 90.2%(406/450)of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore,57.9%(44/76)and 79.1%(356/450)were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 64.6%(370/573),while more than 80.0% of CRAB complex was sensitive to tigecycline,eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 17.0%(99/581). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China,with statistically significant differences in the prevalence of CREC,CRKP,CRPA and CRAB complex( χ2=10.6,28.6,10.8 and 19.3, P<0.05). The prevalence of ESBL-producing Escherichia coli, CREC,CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals( χ2=12.5,9.8,12.7 and 57.8,all P<0.01). Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China,and Escherichia coli is ranked in the top,while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend,CREC infecton maintains a low prevalence level,and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.
7.Construction of a machine learning model based on the Ki67 positive index to predict the recurrence risk of hepatocellular carcinoma
Haoran LI ; Yan YU ; Fangying FAN ; Wenzhen DING ; Hui FENG ; Minghua YING ; Jiawei LI ; Qingqing SUN ; Lele BIAN ; Haokai XU ; Zhanyue CHEN ; Jie YU ; Ping LIANG
Chinese Journal of Hepatology 2025;33(9):898-909
Objective:To screen the optimal machine learning model for predicting the recurrence condition of hepatocellular carcinoma (HCC) at different time points post-surgery, based on the cutoff value of the Ki67 positive proliferation index condition calculated from recurrence-free survival and combined with various clinical features.Methods:retrospective study included initially treated patients with solitary HCC who underwent radical surgery at the Fifth Medical Center of the PLA General Hospital from January 2013 to March 2023. Data included general clinical data, preoperative laboratory parameters, and surgical pathology information about the subjects. The postoperative recurrence status was assessed by querying the medical record system or by telephone follow-up. The Ki67 positive index cutoff value was determined by the X-tile software based on the patient's recurrence-free survival status and time analysis. Survival rates were calculated using the Kaplan-Meier method, and survival curves were plotted. The study population was randomly divided into training and testing groups in a 7:3 ratio using a computer-generated random number method. The minimum redundancy maximum relevance (mRMR) method was used for feature variable selection. Predictive models for postoperative HCC recurrence conditions in patients with HCC were constructed using random forest, support vector machine, logistic regression, and gradient boosting decision tree machine learning algorithms. Inter-group comparisons for continuous data were performed using the t-test or Mann-Whitney U test. Inter-group comparisons of enumeration data were performed using the Pearson χ2 test, continuity-corrected χ2 test, or Fisher's exact test. Results:The cutoff values for the Ki67 positivity index were 0.3 and 0.5 in 510 cases, with a follow-up time ranging from 1.2 to 11.4 years (median: 6.2 years). The recurrence-free survival time was between 1 and 135 months (median: 32 months), with recurrence-free survival rates post-surgery at 1, 2, 3, and 5 years were 87.5%, 77.1%, 61.2%, and 54.5%, respectively. The top five variables predicted HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years, in accordance with information obtained by the mRMR screen out. The Ki67 positivity index screened a successfully constructed machine learning model to predict HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years. The machine learning model based on the gradient boosting decision tree algorithm had the best prediction performance among them (areas under the receiver operating characteristic curves for predicting HCC recurrence within six months in the training and validation sets were 0.996 and 0.946, and accuracies were 0.972 and 0.935, respectively).Conclusion:A machine learning model was successfully constructed using the Ki67 positivity index combined with four readily available clinical features to predict HCC recurrence. The machine learning model based on the gradient boosting decision tree algorithm demonstrated the best performance in terms of predicting HCC recurrence within six months after surgery.
8.National bloodstream infection bacterial resistance surveillance report 2023: Gram-positive bacteria
Chaoqun YING ; Jinru JI ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(2):118-132
Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System(BRICS)during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute(CLSI). Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus( n=1 544,35.2%),coagulase-negative Staphylococci( n=1 441,32.9%), Enterococcus faecium( n=574,13.1%), Enterococcus faecalis( n=385,8.8%),and α-hemolytic Streptococci( n=187,4.3%). The prevalence of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)was 26.2%(405/1 544)and 69.8%(1 006/1 441),respectively. Notably,all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility(>97.0%)to cephalobiol,rifampicin,trimethoprim-sulfamethoxazole,linezolid,minocycline,tigecycline,and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium(resistance to vancomycin and teicoplanin:both 1.7%)compared to Enterococcus faecalis(both 0.3%). The detection rates of MRSA and MRCNS exhibited significant regional variations across the country( χ2=17.674 and 148.650,respectively,both P<0.001). No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA( χ2=14.111, P<0.001)and MRCNS( χ2=4.828, P=0.028)in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA( χ2=18.986, P<0.001)and MRCNS( χ2=4.477, P=0.034)in less developed regions(per capita GDP
9.National bloodstream infection bacterial resistance surveillance report (2023) : Gram-negative bacteria
Jinru JI ; Zhiying LIU ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Jiangqin SONG ; Hui DING ; Yanyan LI ; Yuanyuan DAI ; Haifeng MAO ; Pengpeng TIAN ; Lu WANG ; Yongyun LIU ; Yizheng ZHOU ; Jiliang WANG ; Yan JIN ; Donghong HUANG ; Hongyun XU ; Peng ZHANG ; Xinhua QIANG ; Hong HE ; Lin ZHENG ; Junmin CAO ; Zhou LIU ; Ying HUANG ; Yan GENG ; Haiquan KANG ; Dan LIU ; Guolin LIAO ; Lixia ZHANG ; Fenghong CHEN ; Yanhong LI ; Baohua ZHANG ; Haixin DONG ; Xiaoyan LI ; Donghua LIU ; Qiuying ZHANG ; Xuefei HU ; Liang GUO ; Sijin MAN ; Dijing SONG ; Rong XU ; Youdong YIN ; Kunpeng LIANG ; Aiyun LI ; Zhuo LI ; Hongxia HU ; Guoping LU ; Jinhua LIANG ; Qiang LIU ; Yinqiao DONG ; Jilu SHEN ; Shuyan HU ; Liang LUAN ; Jian LI ; Ling MENG ; Dengyan QIAO ; Xiusan XIA ; Bo QUAN ; Dahong WANG ; Chunhua HAN ; Xiaoping YAN ; Fei LI ; Shifu WANG ; Ping SHEN ; Yunbo CHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2025;18(1):47-62
Objective:To report the results of bacterial resistant investigation collaborative system(BRICS)on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023,and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute(CLSI). WHONET 5.6 and SPSS 25.0 were used to analyze the data.Results:During the study period,11 492 strains of Gram-negative bacteria were collected from 60 hospitals,of which 10 098(87.9%)were Enterobacterales and 1 394(12.1%)were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli(50.0%), Klebsiella pneumoniae(26.1%), Pseudomonas aeruginosa(5.1%), Acinetobacter baumannii complex(5.0%)and Enterobacter cloacae complex(4.1%). The ESBL-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus mirablilis were 46.8%(2 685/5 741),18.3%(549/2 999)and 44.0%(77/175),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(76/5 741)and 15.0%(450/2 999);32.9%(25/76)and 78.0%(351/450)of CREC and CRKP were sensitive to ceftazidime/avibactam combination,respectively. 94.7%(72/76)and 90.2%(406/450)of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore,57.9%(44/76)and 79.1%(356/450)were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 64.6%(370/573),while more than 80.0% of CRAB complex was sensitive to tigecycline,eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 17.0%(99/581). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China,with statistically significant differences in the prevalence of CREC,CRKP,CRPA and CRAB complex( χ2=10.6,28.6,10.8 and 19.3, P<0.05). The prevalence of ESBL-producing Escherichia coli, CREC,CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals( χ2=12.5,9.8,12.7 and 57.8,all P<0.01). Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China,and Escherichia coli is ranked in the top,while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend,CREC infecton maintains a low prevalence level,and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.
10.Safety of high-carbohydrate fluid diet 2 h versus overnight fasting before non-emergency endoscopic retrograde cholangiopancreatography: A single-blind, multicenter, randomized controlled trial
Wenbo MENG ; W. Joseph LEUNG ; Zhenyu WANG ; Qiyong LI ; Leida ZHANG ; Kai ZHANG ; Xuefeng WANG ; Meng WANG ; Qi WANG ; Yingmei SHAO ; Jijun ZHANG ; Ping YUE ; Lei ZHANG ; Kexiang ZHU ; Xiaoliang ZHU ; Hui ZHANG ; Senlin HOU ; Kailin CAI ; Hao SUN ; Ping XUE ; Wei LIU ; Haiping WANG ; Li ZHANG ; Songming DING ; Zhiqing YANG ; Ming ZHANG ; Hao WENG ; Qingyuan WU ; Bendong CHEN ; Tiemin JIANG ; Yingkai WANG ; Lichao ZHANG ; Ke WU ; Xue YANG ; Zilong WEN ; Chun LIU ; Long MIAO ; Zhengfeng WANG ; Jiajia LI ; Xiaowen YAN ; Fangzhao WANG ; Lingen ZHANG ; Mingzhen BAI ; Ningning MI ; Xianzhuo ZHANG ; Wence ZHOU ; Jinqiu YUAN ; Azumi SUZUKI ; Kiyohito TANAKA ; Jiankang LIU ; Ula NUR ; Elisabete WEIDERPASS ; Xun LI
Chinese Medical Journal 2024;137(12):1437-1446
Background::Although overnight fasting is recommended prior to endoscopic retrograde cholangiopancreatography (ERCP), the benefits and safety of high-carbohydrate fluid diet (CFD) intake 2 h before ERCP remain unclear. This study aimed to analyze whether high-CFD intake 2 h before ERCP can be safe and accelerate patients’ recovery.Methods::This prospective, multicenter, randomized controlled trial involved 15 tertiary ERCP centers. A total of 1330 patients were randomized into CFD group ( n = 665) and fasting group ( n = 665). The CFD group received 400 mL of maltodextrin orally 2 h before ERCP, while the control group abstained from food/water overnight (>6 h) before ERCP. All ERCP procedures were performed using deep sedation with intravenous propofol. The investigators were blinded but not the patients. The primary outcomes included postoperative fatigue and abdominal pain score, and the secondary outcomes included complications and changes in metabolic indicators. The outcomes were analyzed according to a modified intention-to-treat principle. Results::The post-ERCP fatigue scores were significantly lower at 4 h (4.1 ± 2.6 vs. 4.8 ± 2.8, t = 4.23, P <0.001) and 20 h (2.4 ± 2.1 vs. 3.4 ± 2.4, t= 7.94, P <0.001) in the CFD group, with least-squares mean differences of 0.48 (95% confidence interval [CI]: 0.26–0.71, P <0.001) and 0.76 (95% CI: 0.57–0.95, P <0.001), respectively. The 4-h pain scores (2.1 ± 1.7 vs. 2.2 ± 1.7, t = 2.60, P = 0.009, with a least-squares mean difference of 0.21 [95% CI: 0.05–0.37]) and positive urine ketone levels (7.7% [39/509] vs. 15.4% [82/533], χ2 = 15.13, P <0.001) were lower in the CFD group. The CFD group had significantly less cholangitis (2.1% [13/634] vs. 4.0% [26/658], χ2 = 3.99, P = 0.046) but not pancreatitis (5.5% [35/634] vs. 6.5% [43/658], χ2 = 0.59, P = 0.444). Subgroup analysis revealed that CFD reduced the incidence of complications in patients with native papilla (odds ratio [OR]: 0.61, 95% CI: 0.39–0.95, P = 0.028) in the multivariable models. Conclusion::Ingesting 400 mL of CFD 2 h before ERCP is safe, with a reduction in post-ERCP fatigue, abdominal pain, and cholangitis during recovery.Trail Registration::ClinicalTrials.gov, No. NCT03075280.

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