1.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.
2.Research advance in preparation and functional modification of porous polytetrafluoroethylene artificial blood vessels
Rong XU ; Haojie WANG ; Mengxiang GENG ; Kai MENG ; Hui WANG ; Keqin ZHANG ; Huijing ZHAO
Chinese Journal of Tissue Engineering Research 2024;28(5):759-765
BACKGROUND:Medium-and large-diameter polytetrafluoroethylene artificial blood vessels have been widely used in clinical practice.However,most of the products were imported from other countries.Small-diameter porous polytetrafluoroethylene vessels are easy to form thrombosis and intimal hyperplasia,resulting in an extremely low long-term patency rate,which is difficult to fulfill clinical requirements. OBJECTIVE:To review and summarize the research progress of polytetrafluoroethylene in the field of artificial blood vessels,which can provide a reference for the functional modification of small-diameter polytetrafluoroethylene artificial blood vessels and the improvement of their long-term patency rate. METHODS:The relevant articles published from October 2022 to March 2023 in CNKI,Web of Science,Wiley Online Library,SpringerLink,Science Direct and IOP Science databases were searched by the first author.The search terms in Chinese were"porous polytetrafluoroethylene,vascular graft,electrospinning,medical application,functional modification".The search terms in English were"ePTFE,porous polytetrafluoroethylene,vascular graft,electrospinning,medical application,functional modification".All the articles about the preparation and modification of polytetrafluoroethylene artificial blood vessels were retrieved. RESULTS AND CONCLUSION:The preparation and functional modification of porous polytetrafluoroethylene artificial blood vessels were still research hotspots and difficult problems.From the research progress in and outside China in recent years,the preparation of porous polytetrafluoroethylene artificial blood vessels mainly adopted the rapid thermal stretching method,but the preparation of polytetrafluoroethylene artificial blood vessels by electrospinning was a promising new method.By analyzing and summarizing different functional modification methods,it was found that the long-term patency rate of porous polytetrafluoroethylene artificial blood vessels had been improved.However,the functional modification of small-diameter polytetrafluoroethylene artificial blood vessels still needed further exploration and optimization.
3.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.
4.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.
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.Diagnostic values of urinary citrate for kidney stones in patients with primary gout.
Yu WANG ; Hui Min ZHANG ; Xue Rong DENG ; Wei Wei LIU ; Lu CHEN ; Ning ZHAO ; Xiao Hui ZHANG ; Zhi Bo SONG ; Yan GENG ; Lan Lan JI ; Yu WANG ; Zhuo Li ZHANG
Journal of Peking University(Health Sciences) 2022;54(6):1134-1140
OBJECTIVE:
To evaluate the relationship between 24 h urinary ion content and kidney stones, and to explore the diagnostic values of kidney stone in primary gout patients.
METHODS:
Patients diagnosed with primary gout had ultrasound scanning of both feet and kidneys in Peking University First Hospital from Jan. 2020 to May 2021. Their clinical characteristics were compared between the positive and negative kidney stone groups, and the relationship between kidney stone and urinary ion composition were analyzed. Risk factors of kidney stone were analyzed. The explored diagnostic values were evaluated for urinary oxalate and citrate according with uric acid kidney stones by dual-energy computed tomography (DECT).
RESULTS:
Among the 100 gouty patients, 80 patients had uric acid crystal deposition in lower joints of extremity by ultrasonography, 61 patients had kidney stone, and 34 had kidney uric acid stones by DECT. All the multiple kidney stones were proved as uric acid kidney stones by DECT. Compared with patients without kidney stone group proved by ultrasonography, patients with kidney stone had longer gouty duration [(48.7±26.6) months vs. (84.0±30.6) months, P=0.01], higher 24 h urinary oxalate [(20.1±9.6) mg vs. (28.6±20.7) mg, P=0.001] and lower 24 h urinary citrate [(506.3±315.4) mg vs. (355.7±219.6) mg, P=0.001]. Compared with the patients without kidney stone by DECT, the patients with uric acid kidney stone also had longer disease duration [(49.1±28.4) months vs. (108.3±72.2) months, P=0.001], higher 24 h urinary oxalate [(23.6±16.9) mg vs. (28.5±18.8) mg, P < 0.05], lower 24 h urinary citrate [(556.0±316.3) mg vs. (391.7±261.2) mg, P < 0.05], higher serum uric acid [(466.2±134.5) μmol/L vs. (517.2±18.1) μmol/L, P < 0.05] and higher 24 h urinary uric acid [(1 518.1±893.4) mg vs. (1 684.2±812.1) mg, P < 0.05]. Logistic regression analysis showed long gout disease duration (OR=1.229, 95%CI: 1.062-1.522, P < 0.05), high serum uric acid level (OR=1.137, 95%CI: 1.001-1.213, P=0.01), low 24 h urinary citrate (OR=0.821, 95%CI: 0.659-0.952, P=0.01) were all risk factors of kidney stones by ultrasonography. Also, long gout disease duration (OR=1.201, 95%CI: 1.101-1.437, P=0.005), high serum creatine uric level (OR=1.145, 95%CI: 1.001-1.182, P=0.04), low 24 h urinary citrate (OR=0.837, 95%CI: 0.739-0.931, P=0.02) were all risk factors of kidney uric acid stones by DECT.
CONCLUSION
Long disease duration and low 24 h urinary citrate were risk factors for kidney stones.
Humans
;
Urinary Calculi
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Uric Acid/analysis*
;
Citric Acid
;
Kidney Calculi/diagnostic imaging*
;
Gout/diagnostic imaging*
;
Citrates
;
Oxalates
7.Revealing characteristics and rules of acupoint sensitization phenomena: based on knee osteoarthritis.
Gui-Xing XU ; Yu-Mei ZHOU ; Ning SUN ; Jin CUI ; Xiao-Rong CHANG ; Lai-Xi JI ; Si-Yu LIU ; Liao-Jun LUO ; Xiao-Jia LIU ; Dan WANG ; Ling ZHAO ; Ding-Jun CAI ; Hui ZHENG ; Ming-Sheng SUN ; Guo-Yan GENG ; Jian CHENG ; Fan-Rong LIANG
Chinese Acupuncture & Moxibustion 2022;42(1):51-57
OBJECTIVE:
To explore the characteristics and rules of acupoint sensitization phenomena based on knee osteoarthritis (KOA), one of the clinical dominant diseases of acupuncture-moxibustion.
METHODS:
In combination with literature and expert experiences, the acupoints with the highest use frequency in treatment of KOA were screened, e.g. Heding (EX-LE 2), Liangqiu (ST 34), Mingmen (GV 4), Neixiyan (EX-LE 4), Ququan (LR 8) and Dubi (ST 35). In 814 patients with KOA and 217 healthy subjects, the acupoint temperature, mechanic pain threshold and pressure pain threshold were detected separately. Using machine learning method, the sensitization was judged at each acupoint.
RESULTS:
Compared with healthy subjects, the acupoint temperature was increased and the mechanic pain threshold and pressure pain threshold were reduced in KOA patients (P<0.05). Besides, the cut-off value was presented to distinguish whether the acupoint was sensitized or not. The results of machine learning showed that the highest prediction accuracy of acupoint sensitization was 86.7% (Shenshu [BL 23]) and the lowest one was 73.9% (Heding [EX LE 2]). The prediction accuracy at the third clinical stage trial was higher, the highest was 93.3% (Ququan [LR 8]) in KOA patients.
CONCLUSION
It is confirmed that the acupoint sensitization reflects the characteristics of disease and is correlative with the conditions of illness, which may provide the reference for the auxiliary diagnosis and condition assessment of KOA.
Acupuncture Points
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Acupuncture Therapy
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Humans
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Moxibustion
;
Osteoarthritis, Knee/therapy*
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Treatment Outcome
8.Benefit of ultrasound in the phenotype recognition of psoriatic arthritis.
Zhi Bo SONG ; Yan GENG ; Xue Rong DENG ; Xiao Hui ZHANG ; Zhuo Li ZHANG
Journal of Peking University(Health Sciences) 2021;53(6):1061-1066
OBJECTIVE:
To explore the difference in phenotype recognition of PsA patients in two clinical scenarios, physical examination with and without ultrasound assessment.
METHODS:
PsA patients who visited the rheumatology and clinical immunology department of Peking University First Hospital between January 2010 and October 2020, with complete data of clinical and ultrasound assessment were enrolled. The phenotypes were first identified based on physical examination only, and then combined with enthesitis and dactylitis shown on power doppler and gray-scale ultrasound. The phenotype groupings without and with ultrasound assessment were presented with Wayne diagram. The distributions of different clinical phenotypes were compared by using χ2 test or Fisher's exact test. The differences of clinical phenotypes with and without ultrasound assessment were compared by using Wilcoxon signed rank test.
RESULTS:
A total of 227 patients with PsA were enrolled with one or more clinical domains. Physical examination revealed that psoriasis was in 209 (92.1%, 209/227) patients, nail involvement in 98 (43.2%, 98/227) patients, peripheral arthritis in 219 (96.5%, 219/227) patients, axial involvement in 25 (11.0%, 25/227) patients, dactylitis in 80 (35.2%, 80/227) patients, and enthesitis in 18 (7.9%, 18/227) patients. Besides 18 patients with clinical enthesitis, ultrasound scan revealed acute enthesitis in 80 patients, with hypoechogenicity (55 cases), tendon thickening (62 cases), and presence of Doppler signals (48 cases). Similarly, dactylitis on ultrasound was found in 18 patients besides those patients with clinical dactylitis. Compared with the phenotypes recognized based on physical examination only, the additional ultrasound assessment revealed that the most common phenotypes, peripheral arthritis was significantly less frequently recognized (49.8% vs. 27.8%, P < 0.001), however on the other hand, the proportion of the patients with peripheral arthritis and enthesitis was significantly increased (4.4% vs. 18.1%, P < 0.001). The phenotype of peripheral arthritis combined with enthesitis, and dactylitis was also dramatically increased (1.8% vs. 17.6%, P < 0.001).
CONCLUSION
Ultrasound is a useful tool to identify enthesitis and dactylitis. With the aid of ultrasound assessment, rheumatologists can better identify the lesions of PsA, accurately identify the phenotypes, and further guide the subsequent treatment.
Arthritis, Psoriatic/diagnostic imaging*
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Humans
;
Phenotype
9.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.
10.BRICS report of 2020: The bacterial composition and antimicrobial resistance profile of clinical isolates from bloodstream infections in China
Yunbo CHEN ; Jinru JI ; Chaoqun YING ; Zhiying LIU ; Qing YANG ; Haishen KONG ; Yuanyuan DAI ; Jiliang WANG ; Haifeng MAO ; Hui DING ; Yongyun LIU ; Yizheng ZHOU ; Hong LU ; Youdong YIN ; Yan JIN ; Hongyun XU ; Lixia ZHANG ; Lu WANG ; Haixin DONG ; Zhenghai YANG ; Fenghong CHEN ; Donghong HUANG ; Guolin LIAO ; Pengpeng TIAN ; Dan LIU ; Yan GENG ; Sijin MAN ; Baohua ZHANG ; Ying HUANG ; Liang GUO ; Junmin CAO ; Beiqing GU ; Yanhong LI ; Hongxia HU ; Liang LUAN ; Shuyan HU ; Lin ZHENG ; Aiyun LI ; Rong XU ; Kunpeng LIANG ; Zhuo LI ; Donghua LIU ; Bo QUAN ; Qiang LIU ; Jilu SHEN ; Yiqun LIAO ; Hai CHEN ; Qingqing BAI ; Xiusan XIA ; Shifu WANG ; Jinhua LIANG ; Liping ZHANG ; Yinqiao DONG ; Xiaoyan QI ; Jianzhong WANG ; Xuefei HU ; Xiaoping YAN ; Dengyan QIAO ; Ling MENG ; Yonghong XIAO
Chinese Journal of Clinical Infectious Diseases 2021;14(6):413-426
Objective:To investigate the bacterial composition and antimicrobial resistance profile of clinical isolates from bloodstream infections in China.Methods:The clinical bacterial strains isolated from blood culture were collected during January 2020 to December 2020 in member hospitals of Blood Bacterial Resistant Investigation Collaborative System (BRICS). Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical Laboratory Standards Institute(CLSI, USA). WHONET 5.6 was used to analyze data.Results:During the study period, 10 043 bacterial strains were collected from 54 hospitals, of which 2 664 (26.5%) were Gram-positive bacteria and 7 379 (73.5%) were Gram-negative bacteria. The top 10 bacterial species were Escherichia coli (38.6%), Klebsiella pneumoniae (18.4%), Staphylococcus aureus (9.9%), coagulase-negative Staphylococci (7.5%), Pseudomonas aeruginosa (3.9%), Enterococcus faecium (3.3%), Enterobacter cloacae (2.8%), Enterococcus faecalis (2.6%), Acinetobacter baumannii (2.4%) and Klebsiella spp (1.8%). The prevalence of methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant coagulase-negative Staphylococcus aureus were 27.6% and 74.4%, respectively. No glycopeptide- and daptomycin-resistant Staphylococci were detected. More than 95% of Staphylococcus aureus were sensitive to rifampicin and SMZco. No vancomycin-resistant Enterococci strains were detected. Extended spectrum β-lactamase (ESBL) producing Escherichia coli, Klebsiella pneumoniae and Proteus mirabilis were 48.4%, 23.6% and 36.1%, respectively. The prevalence rates of carbapenem-resistance in Escherichia coli and Klebsiella pneumoniae were 2.3% and 16.1%, respectively; 9.6% of carbapenem-resistant Klebsiella pneumoniae strains were resistant to ceftazidime/avibactam combination. The prevalence rate of carbapenem-resistance in Acinetobacter baumannii was 60.0%, while polymyxin and tigecycline showed good activity against Acinetobacter baumannii. The prevalence rate of carbapenem-resistance of Pseudomonas aeruginosa was 23.2%. Conclusions:The surveillance results in 2020 showed that the main pathogens of bloodstream infection in China were gram-negative bacteria, while Escherichia coli was the most common pathogen, and ESBL-producing strains declined while carbapenem-resistant Klebsiella pneumoniae kept on high level. The proportion and the prevalence of carbapenem-resistant Pseudomonas aeruginosa were on the rise slowly. On the other side, the MRSA incidence got lower in China, while the overall prevalence of vancomycin-resistant Enterococci was low.

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