1.National bloodstream infection bacterial resistance surveillance report (2022) : Gram-negative bacteria
Zhiying LIU ; Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Haifeng MAO ; Hui DING ; Pengpeng TIAN ; Jiangqin SONG ; Yongyun LIU ; Jiliang WANG ; Yan JIN ; Yuanyuan DAI ; Yizheng ZHOU ; Yan GENG ; Fenghong CHEN ; Lu WANG ; Yanyan LI ; Dan LIU ; Peng ZHANG ; Junmin CAO ; Xiaoyan LI ; Dijing SONG ; Xinhua QIANG ; Yanhong LI ; Qiuying ZHANG ; Guolin LIAO ; Ying HUANG ; Baohua ZHANG ; Liang GUO ; Aiyun LI ; Haiquan KANG ; Donghong HUANG ; Sijin MAN ; Zhuo LI ; Youdong YIN ; Kunpeng LIANG ; Haixin DONG ; Donghua LIU ; Hongyun XU ; Yinqiao DONG ; Rong XU ; Lin ZHENG ; Shuyan HU ; Jian LI ; Qiang LIU ; Liang LUAN ; Jilu SHEN ; Lixia ZHANG ; Bo QUAN ; Xiaoping YAN ; Xiaoyan QI ; Dengyan QIAO ; Weiping LIU ; Xiusan XIA ; Ling MENG ; Jinhua LIANG ; Ping SHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2024;17(1):42-57
Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System(BRICS)were collected during January 2022 to December 2022. 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 software were used to analyze the data.Results:During the study period,9 035 strains of Gram-negative bacteria were collected from 51 hospitals,of which 7 895(87.4%)were Enterobacteriaceae and 1 140(12.6%)were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli( n=4 510,49.9%), Klebsiella pneumoniae( n=2 340,25.9%), Pseudomonas aeruginosa( n=534,5.9%), Acinetobacter baumannii complex( n=405,4.5%)and Enterobacter cloacae( n=327,3.6%). The ESBLs-producing rates in Escherichia coli, Klebsiella pneumoniae and Proteus spp. were 47.1%(2 095/4 452),21.0%(427/2 033)and 41.1%(58/141),respectively. The prevalence of carbapenem-resistant Escherichia coli(CREC)and carbapenem-resistant Klebsiella pneumoniae(CRKP)were 1.3%(58/4 510)and 13.1%(307/2 340);62.1%(36/58)and 9.8%(30/307)of CREC and CRKP were resistant to ceftazidime/avibactam combination,respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)complex was 59.5%(241/405),while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa(CRPA)was 18.4%(98/534). There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions,with statistically significant differences in the prevalence of CRKP and CRPA( χ2=20.489 and 20.252, P<0.001). The prevalence of CREC,CRKP,CRPA,CRAB,ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals( χ2=11.953,81.183,10.404,5.915,12.415 and 6.459, P<0.01 or <0.05),while the prevalence of CRPA was higher in economically developed regions(per capita GDP ≥ 92 059 Yuan)than that in economically less-developed regions(per capita GDP <92 059 Yuan)( χ2=6.240, P=0.012). Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend,and Escherichia coli is ranked in the top,while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different,and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.
2.National bloodstream infection bacterial resistance surveillance report(2022): Gram-positive bacteria
Chaoqun YING ; Yunbo CHEN ; Jinru JI ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Haifeng MAO ; Hui DING ; Pengpeng TIAN ; Jiangqin SONG ; Yongyun LIU ; Jiliang WANG ; Yan JIN ; Yuanyuan DAI ; Yizheng ZHOU ; Yan GENG ; Fenghong CHEN ; Lu WANG ; Yanyan LI ; Dan LIU ; Peng ZHANG ; Junmin CAO ; Xiaoyan LI ; Dijing SONG ; Xinhua QIANG ; Yanhong LI ; Qiuying ZHANG ; Guolin LIAO ; Ying HUANG ; Baohua ZHANG ; Liang GUO ; Aiyun LI ; Haiquan KANG ; Donghong HUANG ; Sijin MAN ; Zhuo LI ; Youdong YIN ; Kunpeng LIANG ; Haixin DONG ; Donghua LIU ; Hongyun XU ; Yinqiao DONG ; Rong XU ; Lin ZHENG ; Shuyan HU ; Jian LI ; Qiang LIU ; Liang LUAN ; Jilu SHEN ; Lixia ZHANG ; Bo QUAN ; Xiaoping YAN ; Xiaoyan QI ; Dengyan QIAO ; Weiping LIU ; Xiusan XIA ; Ling MENG ; Jinhua LIANG ; Ping SHEN ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2024;17(2):99-112
Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-positive bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-positive bacteria from blood cultures in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System(BRICS)were collected during January 2022 to December 2022. 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 software were used to analyze the data.Results:A total of 3 163 strains of Gram-positive pathogens were collected from 51 member units,and the top five bacteria were Staphylococcus aureus( n=1 147,36.3%),coagulase-negative Staphylococci( n=928,29.3%), Enterococcus faecalis( n=369,11.7%), Enterococcus faecium( n=296,9.4%)and alpha-hemolyticus Streptococci( n=192,6.1%). The detection rates of methicillin-resistant Staphylococcus aureus(MRSA)and methicillin-resistant coagulase-negative Staphylococci(MRCNS)were 26.4%(303/1 147)and 66.7%(619/928),respectively. No glycopeptide and daptomycin-resistant Staphylococci were detected. The sensitivity rates of Staphylococcus aureus to cefpirome,rifampin,compound sulfamethoxazole,linezolid,minocycline and tigecycline were all >95.0%. Enterococcus faecium was more prevalent than Enterococcus faecalis. The resistance rates of Enterococcus faecium to vancomycin and teicoplanin were both 0.5%(2/369),and no vancomycin-resistant Enterococcus faecium was detected. The detection rate of MRSA in southern China was significantly lower than that in other regions( χ2=14.578, P=0.002),while the detection rate of MRCNS in northern China was significantly higher than that in other regions( χ2=15.195, P=0.002). The detection rates of MRSA and MRCNS in provincial hospitals were higher than those in municipal hospitals( χ2=13.519 and 12.136, P<0.001). The detection rates of MRSA and MRCNS in economically more advanced regions(per capita GDP≥92 059 Yuan in 2022)were higher than those in economically less advanced regions(per capita GDP<92 059 Yuan)( χ2=9.969 and 7.606, P=0.002和0.006). Conclusions:Among the Gram-positive pathogens causing bloodstream infections in China, Staphylococci is the most common while the MRSA incidence decreases continuously with time;the detection rate of Enterococcus faecium exceeds that of Enterococcus faecalis. The overall prevalence of vancomycin-resistant Enterococci is still at a low level. The composition ratio of Gram-positive pathogens and resistant profiles varies slightly across regions of China,with the prevalence of MRSA and MRCNS being more pronounced in provincial hospitals and areas with a per capita GDP≥92 059 yuan.
3.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
4.Microstructure and mechanical properties of hernia mesh
Zhaoning GENG ; Dongming YIN ; Lin MAO ; Chengli SONG
International Journal of Biomedical Engineering 2023;46(4):300-305
Objective:The microstructure, tensile strength, and bursting strength of different brands of hernia meshes were compared and analyzed through experiments to evaluate the performance of different meshes.Methods:The balance and microscope were used to test the weight and microstructure of 15 common meshes and the tensile testing machine and burst testing machine were used to test the tensile and bursting properties of the mesh, and the mechanical properties of the mesh were analyzed.Results:The woven structures of the mesh are diamond, polygon and circle. The average weight of inguinal meshes is 0.08 mg/mm 2, and the average weight of abdominal wall hernia meshes is 0.18 mg/mm 2. The wire diameters of G3 - G6 meshes are larger, while the mesh opening ratio of G12 is lower. In the tensile performance test, it is known that G15 has the highest tensile strength, G12 and G14 have lower tensile strengths in lightweight meshes, and G1, G2, and G7 have lower tensile strengths in lightweight meshes. In the burst performance test, it is known that G3, G9, and G15 have the highest burst strength, while G12, G13, and G14 have the lowest burst strength in lightweight meshes. G1, G2, and G4 have the lowest burst strength in lightweight meshes. Conclusions:The mesh with a polygonal mesh and a large mesh opening ratio has better mechanical properties. The results of this study provide experimental evidence for optimizing hernia meshes, which is expected to provide better support for related research and applications.
5.BRICS report of 2021: The distribution and antimicrobial resistance profile of clinical bacterial isolates from blood stream infections in China
Yunbo CHEN ; Jinru JI ; Zhiying LIU ; Chaoqun YING ; Qing YANG ; Haishen KONG ; Jiliang WANG ; Hui DING ; Haifeng MAO ; Yizheng ZHOU ; Yan JIN ; Yongyun LIU ; Yan GENG ; Yuanyuan DAI ; Hong LU ; Peng ZHANG ; Ying HUANG ; Donghong HUANG ; Xinhua QIANG ; Jilu SHEN ; Hongyun XU ; Fenghong CHEN ; Guolin LIAO ; Dan LIU ; Haixin DONG ; Jiangqin SONG ; Lu WANG ; Junmin CAO ; Lixia ZHANG ; Yanhong LI ; Dijing SONG ; Zhuo LI ; Youdong YIN ; Donghua LIU ; Liang GUO ; Qiang LIU ; Baohua ZHANG ; Rong XU ; Yinqiao DONG ; Shuyan HU ; Kunpeng LIANG ; Bo QUAN ; Lin ZHENG ; Ling MENG ; Liang LUAN ; Jinhua LIANG ; Weiping LIU ; Xuefei HU ; Pengpeng TIAN ; Xiaoping YAN ; Aiyun LI ; Jian LI ; Xiusan XIA ; Xiaoyan QI ; Dengyan QIAO ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2023;16(1):33-47
Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical bacterial isolates from bloodstream infections in China in 2021.Methods:The clinical bacterial strains isolated from blood culture from member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS) were collected during January 2021 to December 2021. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical Laboratory Standards Institute (CLSI). WHONET 5.6 was used to analyze data.Results:During the study period, 11 013 bacterial strains were collected from 51 hospitals, of which 2 782 (25.3%) were Gram-positive bacteria and 8 231 (74.7%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (37.6%), Klebsiella pneumoniae (18.9%), Staphylococcus aureus (9.8%), coagulase-negative Staphylococci (6.3%), Pseudomonas aeruginosa (3.6%), Enterococcus faecium (3.6%), Acinetobacter baumannii (2.8%), Enterococcus faecalis (2.7%), Enterobacter cloacae (2.5%) and Klebsiella spp (2.1%). The prevalence of methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus aureus were 25.3% and 76.8%, respectively. No glycopeptide- and daptomycin-resistant Staphylococci was detected; more than 95.0% of Staphylococcus aureus were sensitive to ceftobiprole. No vancomycin-resistant Enterococci strains were detected. The rates of extended spectrum B-lactamase (ESBL)-producing isolated in Escherichia coli, Klebsiella pneumoniae and Proteus mirabilis were 49.6%, 25.5% and 39.0%, respectively. The prevalence rates of carbapenem-resistance in Escherichia coli and Klebsiella pneumoniae were 2.2% and 15.8%, respectively; 7.9% of carbapenem-resistant Klebsiella pneumoniae was resistant to ceftazidime/avibactam combination. Ceftobiprole demonstrated excellent activity against non-ESBL-producing Escherichia coli and Klebsiella pneumoniae. Aztreonam/avibactam was highly active against carbapenem-resistant Escherichia coli and Klebsiella pneumoniae. The prevalence rate of carbapenem-resistance in Acinetobacter baumannii was 60.0%, while polymyxin and tigecycline showed good activity against Acinetobacter baumannii (5.5% and 4.5%). The prevalence of carbapenem-resistance in Pseudomonas aeruginosa was 18.9%. Conclusions:The BRICS surveillance results in 2021 shows that the main pathogens of blood stream infection in China are gram-negative bacteria, in which Escherichia coli is the most common. The MRSA incidence shows a further decreasing trend in China and the overall prevalence of vancomycin-resistant Enterococci is low. The prevalence of Carbapenem-resistant Klebsiella pneumoniae is still on a high level, but the trend is downwards.
6.A nomogram for preoperative prediction of lymph node metastasis in patients with intrahepatic cholangiocarcinoma based on inflammation-related markers.
Xiao Peng YU ; Jia Lu CHEN ; Yue TANG ; Chen CHEN ; Ying Hong QIU ; Hong WU ; Tian Qiang SONG ; Yu HE ; Xian Hai MAO ; Wen Long ZHAI ; Zhang Jun CHENG ; Xiao LIANG ; Jing Dong LI ; Chuan Dong SUN ; Kai MA ; Rui Xin LIN ; Zhi Min GENG ; Zhao Hui TANG ; Zhi Wei QUAN
Chinese Journal of Surgery 2023;61(4):321-329
Objectives: To construct a nomogram for prediction of intrahepatic cholangiocarcinoma (ICC) lymph node metastasis based on inflammation-related markers,and to conduct its clinical verification. Methods: Clinical and pathological data of 858 ICC patients who underwent radical resection were retrospectively collected at 10 domestic tertiary hospitals in China from January 2010 to December 2018. Among the 508 patients who underwent lymph node dissection,207 cases had complete variable clinical data for constructing the nomogram,including 84 males,123 females,109 patients≥60 years old,98 patients<60 years old and 69 patients were pathologically diagnosed with positive lymph nodes after surgery. Receiver operating characteristic curve was drawn to calculate the accuracy of preoperative imaging examinations to determine lymph node status,and the difference in overall survival time was compared by Log-rank test. Partial regression squares and statistically significant preoperative variables were screened by backward stepwise regression analysis. R software was applied to construct a nomogram,clinical decision curve and clinical influence curve,and Bootstrap method was used for internal verification. Moreover,retrospectively collecting clinical information of 107 ICC patients with intraoperative lymph node dissection admitted to 9 tertiary hospitals in China from January 2019 to June 2021 was for external verification to verify the accuracy of the nomogram. 80 patients with complete clinical data but without lymph node dissection were divided into lymph node metastasis high-risk group and low-risk group according to the score of the nomogram among the 858 patients. Log-rank test was used to compare the overall survival of patients with or without lymph node metastasis diagnosed by pathology. Results: The area under the curve of preoperative imaging examinations for lymph node status assessment of 440 patients was 0.615,with a false negative rate of 62.8% (113/180) and a false positive rate of 14.2% (37/260). The median survival time of 207 patients used to construct a nomogram with positive or negative postoperative pathological lymph node metastases was 18.5 months and 27.1 months,respectively (P<0.05). Five variables related to lymph node metastasis were screened out by backward stepwise regression analysis,which were combined calculi,neutrophil/lymphocyte ratio,albumin,liver capsule invasion and systemic immune inflammation index,according to which a nomogram was constructed with concordance index(C-index) of 0.737 (95%CI: 0.667 to 0.806). The C-index of external verification was 0.674 (95%CI:0.569 to 0.779). The calibration prediction curve was in good agreement with the reference curve. The results of the clinical decision curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.32,the maximum net benefit could be obtained by 0.11,and the cost/benefit ratio was 1∶2. The results of clinical influence curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.6,the probability of correctly predicting lymph node metastasis could reach more than 90%. There was no significant difference in overall survival time between patients with high/low risk of lymph node metastasis assessed by the nomogram and those with pathologically confirmed lymph node metastasis or without lymph node metastasis (Log-rank test:P=0.082 and 0.510,respectively). Conclusion: The prediction accuracy of preoperative nomogram for ICC lymph node metastasis based on inflammation-related markers is satisfactory,which can be used as a supplementary method for preoperative diagnosis of lymph node metastasis and is helpful for clinicians to make personalized decision of lymph node dissection for patients with ICC.
7.The analysis of long-term prognostic factors after laparoscopic liver resection for intrahepatic cholangiocarcinoma and establishment of survival Nomogram model.
Ze Feng SHEN ; Chen CHEN ; Zhi Min GENG ; Xian Hai MAO ; Jing Dong LI ; Tian Qiang SONG ; Chuan Dong SUN ; Hong WU ; Zhang Jun CHENG ; Rui Xin LIN ; Yu HE ; Wen Long ZHAI ; Di TANG ; Zhao Hui TANG ; Xiao LIANG
Chinese Journal of Surgery 2022;60(10):939-947
Objective: To establish a survival prediction model based on the independent prognostic factors of long-term prognosis after laparoscopic liver resection(LLR) for intrahepatic cholangiocarcinoma(ICC). Methods: The clinical and pathological data of 351 consecutive patients with ICC who received radical LLR in 13 Chinese medical centers from August 2010 to May 2021 were collected retrospectively. There were 190 males and 161 females,aged(M(IQR)) 61(14)years(range:23 to 93 years). The total cohort was randomly divided into a training dataset(264 cases) and a validation dataset(87 cases). The patients were followed up by outpatient service or telephone,and the deadline for follow-up was October 2021. Based on the training dataset,the multivariate Cox proportional hazards regression model was used to screen the independent influencing factors of long-term prognosis to construct a Nomogram model. The Nomogram model's discrimination,calibration,and clinical benefit were evaluated through internal and external validation,and an assessment of the overall value of two groups was made through the use of a receiver operating characteristic(ROC) curve. Results: There was no significant difference in clinical and pathological characteristics and long-term survival results between the training and validation datasets(all P>0.05). The multivariate Cox analysis showed that CA19-9,CA125,conversion to laparotomy during laparoscopic surgery,and lymph node metastasis were independent prognostic factors for ICC patients after LLR(all P<0.05). The survival Nomogram was established based on the independent prognostic factors obtained from the above screening. The ROC curve showed that the area under the curve of 1, 3 and 5-year overall survival rates of patients in the training dataset were 0.794(95%CI:0.721 to 0.867),0.728(95%CI:0.618 to 0.839) and 0.799(95%CI:0.670 to 0.928),and those in the validation dataset were 0.787(95%CI:0.660 to 0.915),0.831(95%CI:0.678 to 0.983) and 0.810(95%CI:0.639 to 0.982). Internal and external validation proved that the model exhibited a certain discrimination,calibration,and clinical applicability. Conclusion: The survival Nomogram model based on the independent influencing factors of long-term prognosis after LLR for ICC(including CA19-9,CA125,conversion to laparotomy during laparoscopic surgery,and lymph node metastasis) exhibites a certain differentiation,calibration,and clinical practicability.
Bile Duct Neoplasms/surgery*
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Bile Ducts, Intrahepatic/pathology*
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CA-19-9 Antigen
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Cholangiocarcinoma/diagnosis*
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Female
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Humans
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Laparoscopy
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Lymphatic Metastasis
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Male
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Nomograms
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Prognosis
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Retrospective Studies
8.Effect of hypochloric acid on Escherichia coli biofilm and the clinical efficacy of hypochloric acid for wounds with Escherichia coli infection.
Jiang LIU ; Bao Lin WU ; Wan Zhao ZHU ; Jie LIU ; Tong WANG ; Mao Mao GENG ; Li BAI ; Yi LIU
Chinese Journal of Burns 2022;38(3):242-250
Objective: To investigate the effect of hypochloric acid on Escherichia coli biofilm and the clinical efficacy of hypochloric acid for wounds with Escherichia coli infection. Methods: One strain of Escherichia coli with the strongest bacterial biofilm forming ability among the strains isolated from specimens in 25 patients (16 males and 9 females, aged 32-67 years) from five clinical departments of the 940th Hospital of the Joint Logistic Support Force was collected for the experimental study from September to December 2019. The Escherichia coli was cultured with hypochloric acid at 162.96, 81.48, 40.74, 20.37, 10.18, 5.09, 2.55, 1.27, 0.64, and 0.32 μg/mL respectively to screen the minimum bactericidal concentration (MBC) of hypochloric acid. The Escherichia coli was cultured with hypochloric acid at the screened MBC for 2, 5, 10, 20, 30, and 60 min respectively to screen the shortest bactericidal time of hypochloric acid. The biofilm formation of Escherichia coli was observed by scanning electron microscopy at 6, 12, 24, 48, 72, and 96 h of incubation, respectively. After 72 h of culture, hypochloric acid at 1, 2, 4, 8, and 16 times of MBC was respectively added to Escherichia coli to screen the minimum biofilm eradicate concentration (MBEC) of hypochloric acid against Escherichia coli. After hypochloric acid at 1, 2, 4, and 8 times of MBEC and sterile saline were respectively added to Escherichia coli for 10 min, the live/dead bacterial staining kit was used to detect the number of live and dead cells, with the rate of dead bacteria calculated (the number of samples was 5). From January to December 2020, 41 patients with infectious wounds meeting the inclusion criteria and admitted to the Department of Burns and Plastic Surgery of the 940th Hospital of Joint Logistic Support Force of PLA were included into the prospective randomized controlled trial. The patients were divided into hypochloric acid group with 21 patients (13 males and 8 females, aged (46±14) years) and povidone iodine group with 20 patients (14 males and 6 females, aged (45±19) years) according to the random number table. Patients in the 2 groups were respectively dressed with sterile gauze soaked with hypochloric acid of 100 μg/mL and povidone iodine solution of 50 mg/mL with the dressings changed daily. Before the first dressing change and on the 10th day of dressing change, tissue was taken from the wound and margin of the wound for culturing bacteria by agar culture method and quantifying the number of bacteria. The amount of wound exudate and granulation tissue growth were observed visually and scored before the first dressing change and on the 3rd, 7th, and 10th days of dressing change. Data were statistically analyzed with one-way analysis of variance, Dunnett-t test, independent sample t test, Mann-Whitney U test, Wilcoxon signed-rank test, chi-square test, or Fisher's exact probability test. Results: The MBC of hypochloric acid against Escherichia coli was 10.18 μg/mL, and the shortest bactericidal time of hypochloric acid with MBC against Escherichia coli was 2 min. Escherichia coli was in a completely free state after 6 and 12 h of culture and gradually aggregated and adhered with the extension of culture time, forming a mature biofilm at 72 h of culture. The MBEC of hypochloric acid against Escherichia coli was 20.36 μg/mL. The Escherichia coli mortality rates after incubation with hypochloric acid at 1, 2, 4, and 8 times of MBEC for 10 min were significantly higher than that after incubation with sterile saline (with t values of 6.11, 25.04, 28.90, and 40.74, respectively, P<0.01). The amount of bacteria in the wound tissue of patients in hypochloric acid group on the 10th day of dressing change was 2.61 (2.20, 3.30)×104 colony forming unit (CFU)/g, significantly less than 4.77 (2.18, 12.48)×104 CFU/g in povidone iodine group (Z=2.06, P<0.05). The amounts of bacteria in the wound tissue of patients in hypochloric acid group and povidone iodine group on the 10th day of dressing change were significantly less than 2.97 (2.90, 3.04)×106 and 2.97 (1.90, 7.95)×106 CFU/g before the first dressing change (with Z values of 4.02 and 3.92, respectively, P<0.01). The score of wound exudate amount of patients in hypochloric acid group on the 10th day of dressing change was significantly lower than that in povidone iodine group (Z=2.07, P<0.05). Compared with those before the first dressing change, the scores of wound exudate amount of patients in hypochloric acid group on the 7th and 10th days of dressing change were significantly decreased (with Z values of -3.99 and -4.12, respectively, P<0.01), and the scores of wound exudate amount of patients in povidone iodine group on the 7th and 10th days of dressing change were significantly decreased (with Z values of -3.54 and -3.93, respectively, P<0.01). The score of wound granulation tissue growth of patients in hypochloric acid group on the 10th day of dressing change was significantly higher than that in povidone iodine group (Z=2.02, P<0.05). Compared with those before the first dressing change, the scores of wound granulation tissue growth of patients in hypochloric acid group on the 7th and 10th days of dressing change were significantly increased (with Z values of -3.13 and -3.67, respectively, P<0.01), and the scores of wound granulation tissue growth of patients in povidone iodine group on the 7th and 10th days of dressing change were significantly increased (with Z values of -3.12 and -3.50, respectively, P<0.01). Conclusions: Hypochloric acid can kill Escherichia coli both in free and biofilm status. Hypochloric acid at a low concentration shows a rapid bactericidal effect on mature Escherichia coli biofilm, and the higher the concentration of hypochloric acid, the better the bactericidal effect. The hypochloric acid of 100 μg/mL is effective in reducing the bacterial load on wounds with Escherichia coli infection in patients, as evidenced by a reduction in wound exudate and indirect promotion of granulation tissue growth, which is more effective than povidone iodine, the traditional topical antimicrobial agent.
Adult
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Aged
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Biofilms
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Escherichia coli
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Escherichia coli Infections/drug therapy*
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Female
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Humans
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Male
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Middle Aged
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Prospective Studies
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Surgical Wound Infection
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Treatment Outcome
9.Comparison of macrolide resistance, molecular characteristics and MAST types of Bordetella pertussis collected from Xi’an and Shanghai
Juansheng ZHANG ; Diqiang ZHANG ; Chen LIN ; Ling CHANG ; Chaofeng MA ; Baozhong CHEN ; Mao GENG
Journal of Xi'an Jiaotong University(Medical Sciences) 2022;43(5):691-696
【Objective】 To compare the macrolide resistance, molecular characteristics and multilocus antigen sequence typing (MAST) of Bordetella pertussis (Bp) collected from Xi’an and Shanghai so as to provide reference for prevention of pertussis and optimize vaccination strategies. 【Methods】 Erythromycin, azithromycin and clarithromycin susceptibility of clinical isolates collected from Xi’an and Shanghai during 2018 and 2019 were determined by E-test. PCR was used to detect the drug-resistant genes and mutation sites. MAST was employed to do molecular typing for the strains. The differences in macrolide resistance and MAST types between Xi’an and Shanghai were compared. 【Results】 Totally 34 strains from Xi’an and 26 strains from Shanghai were isolated. There were differences between Xi’an and Shanghai in the macrolide resistance (χ2=13.650, P<0.001). The composition ratio of MAST types of pertussis strains was also different between Xi’an and Shanghai (χ2=18.642, P<0.001) in that the prn1/ptxP1/ptxA1/fim3-1/fim2-1 strains dominated in Xi’an, while the prn1/ptxP1/ptxA1/fim3-1/fim2-1 and prn2/ptxP3/ptxA1/fim3-1/fim2-1 were almost half and half in Shanghai. A2047G site mutation was detected in all the macrolide-resistant strains, but not in all sensitive strains. Methylase genes ermA and ermB were detected in some macrolide-resistant strains. No other macrolide-resistant genes were found in resistant strains and no mutation or drug resistance gene was found in all the susceptible strains. 【Conclusion】 Differences existed between Xi’an and Shanghai in the macrolide resistance and MAST types of Bordetella pertussis strains. Further monitoring of Bordetella pertussis in China is required to better understand the resistance and evolution of the pathogen.
10.Establishment of an auxiliary diagnosis system of newborn screening for inherited metabolic diseases based on artificial intelligence technology and a clinical trial
Rulai YANG ; Yanling YANG ; Ting WANG ; Weize XU ; Gang YU ; Jianbin YANG ; Qiaoling SUN ; Maosheng GU ; Haibo LI ; Dehua ZHAO ; Juying PEI ; Tao JIANG ; Jun HE ; Hui ZOU ; Xinmei MAO ; Guoxing GENG ; Rong QIANG ; Guoli TIAN ; Yan WANG ; Hongwei WEI ; Xiaogang ZHANG ; Hua WANG ; Yaping TIAN ; Lin ZOU ; Yuanyuan KONG ; Yuxia ZHOU ; Mingcai OU ; Zerong YAO ; Yulin ZHOU ; Wenbin ZHU ; Yonglan HUANG ; Yuhong WANG ; Cidan HUANG ; Ying TAN ; Long LI ; Qing SHANG ; Hong ZHENG ; Shaolei LYU ; Wenjun WANG ; Yan YAO ; Jing LE ; Qiang SHU
Chinese Journal of Pediatrics 2021;59(4):286-293
Objective:To establish a disease risk prediction model for the newborn screening system of inherited metabolic diseases by artificial intelligence technology.Methods:This was a retrospectively study. Newborn screening data ( n=5 907 547) from February 2010 to May 2019 from 31 hospitals in China and verified data ( n=3 028) from 34 hospitals of the same period were collected to establish the artificial intelligence model for the prediction of inherited metabolic diseases in neonates. The validity of the artificial intelligence disease risk prediction model was verified by 360 814 newborns ' screening data from January 2018 to September 2018 through a single-blind experiment. The effectiveness of the artificial intelligence disease risk prediction model was verified by comparing the detection rate of clinically confirmed cases, the positive rate of initial screening and the positive predictive value between the clinicians and the artificial intelligence prediction model of inherited metabolic diseases. Results:A total of 3 665 697 newborns ' screening data were collected including 3 019 cases ' positive data to establish the 16 artificial intelligence models for 32 inherited metabolic diseases. The single-blind experiment ( n=360 814) showed that 45 clinically diagnosed infants were detected by both artificial intelligence model and clinicians. A total of 2 684 cases were positive in tandem mass spectrometry screening and 1 694 cases were with high risk in artificial intelligence prediction model of inherited metabolic diseases, with the positive rates of tandem 0.74% (2 684/360 814)and 0.46% (1 694/360 814), respectively. Compared to clinicians, the positive rate of newborns was reduced by 36.89% (990/2 684) after the application of the artificial intelligence model, and the positive predictive values of clinicians and artificial intelligence prediction model of inherited metabolic diseases were 1.68% (45/2 684) and 2.66% (45/1 694) respectively. Conclusion:An accurate, fast, and the lower false positive rate auxiliary diagnosis system for neonatal inherited metabolic diseases by artificial intelligence technology has been established, which may have an important clinical value.

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