1.Differential Analysis of Oral Microbiota in db/db Mouse Model of Type 2 Diabetes Utilizing 16S rRNA Sequencing
Qianjia PAN ; Junyi GE ; Nan HU ; Fei HUA ; Min GU
Laboratory Animal and Comparative Medicine 2025;45(2):147-157
Objective To investigate the changes in oral microbiota of db/db mice and provide an experimental basis for exploring the relationship between type 2 diabetes mellitus and oral microecology.Methods Eight 10-week-old male db/db mice were designated as the diabetes experimental group(db/db group),while eight 10-week-old male db/m mice were assigned as the normal control group(db/m group).After a 5-day adaptive feeding period,tail venous blood samples were collected on the 6th and 37th days,and fasting blood glucose(FBG)levels and oral glucose tolerance test(OGTT)were performed for both groups to verify the reliability of the diabetes model.On the 15th day of feeding with the same diet,oral microbiota samples were collected from the buccal mucosa,dorsal and ventral tongue surfaces,oral floor mucosa,hard palate mucosa,and the gingival areas of both the upper and lower jaws of the two groups.Genomic DNA from the oral microbiota was extracted,and the V3-V4 regions of the 16S ribosomal RNA(16S rRNA)gene were amplified using a GeneAmp 9700 thermocycler.The composition of the oral microbiota was evaluated through double-labelled amplification and sequencing on the Illumina MiSeq platform,followed by bioinformatics analysis using QI I ME software(version 1.6.0).Results The FBG levels and OGTT results on the 6th and 37th days after the start of the experiment indicated that db/db mice exhibited more pronounced symptoms of type 2 diabetes compared to db/m mice.Alpha diversity(αdiversity)analysis showed no significant difference in the diversity of oral microbiota between the two groups(P>0.05);however,there was a significant difference in richness(P<0.05).Principal coordinate analysis(PCoA)revealed differences in the oral microbiota composition between the db/db group and db/m group(P<0.05).Species composition analysis and LEfSe analysis demonstrated that the relative abundance of oral microbiota in db/db group mice,predominantly composed of p_Proteobacteria,increased significantly at the phylum level(P<0.05).At the genus level,the relative abundances of g_Proteus and g_Enterococcus showed a significant increase(P<0.001).Conclusion The composition and diversity of oral microbiota in db/db mice with type 2 diabetes mellitus significantly differed from those without the disease.
2.Differential Analysis of Oral Microbiota in db/db Mouse Model of Type 2 Diabetes Utilizing 16S rRNA Sequencing
Qianjia PAN ; Junyi GE ; Nan HU ; Fei HUA ; Min GU
Laboratory Animal and Comparative Medicine 2025;45(2):147-157
Objective To investigate the changes in oral microbiota of db/db mice and provide an experimental basis for exploring the relationship between type 2 diabetes mellitus and oral microecology.Methods Eight 10-week-old male db/db mice were designated as the diabetes experimental group(db/db group),while eight 10-week-old male db/m mice were assigned as the normal control group(db/m group).After a 5-day adaptive feeding period,tail venous blood samples were collected on the 6th and 37th days,and fasting blood glucose(FBG)levels and oral glucose tolerance test(OGTT)were performed for both groups to verify the reliability of the diabetes model.On the 15th day of feeding with the same diet,oral microbiota samples were collected from the buccal mucosa,dorsal and ventral tongue surfaces,oral floor mucosa,hard palate mucosa,and the gingival areas of both the upper and lower jaws of the two groups.Genomic DNA from the oral microbiota was extracted,and the V3-V4 regions of the 16S ribosomal RNA(16S rRNA)gene were amplified using a GeneAmp 9700 thermocycler.The composition of the oral microbiota was evaluated through double-labelled amplification and sequencing on the Illumina MiSeq platform,followed by bioinformatics analysis using QI I ME software(version 1.6.0).Results The FBG levels and OGTT results on the 6th and 37th days after the start of the experiment indicated that db/db mice exhibited more pronounced symptoms of type 2 diabetes compared to db/m mice.Alpha diversity(αdiversity)analysis showed no significant difference in the diversity of oral microbiota between the two groups(P>0.05);however,there was a significant difference in richness(P<0.05).Principal coordinate analysis(PCoA)revealed differences in the oral microbiota composition between the db/db group and db/m group(P<0.05).Species composition analysis and LEfSe analysis demonstrated that the relative abundance of oral microbiota in db/db group mice,predominantly composed of p_Proteobacteria,increased significantly at the phylum level(P<0.05).At the genus level,the relative abundances of g_Proteus and g_Enterococcus showed a significant increase(P<0.001).Conclusion The composition and diversity of oral microbiota in db/db mice with type 2 diabetes mellitus significantly differed from those without the disease.
3.GPR40 novel agonist SZZ15-11 regulates glucolipid metabolic disorders in spontaneous type 2 diabetic KKAy mice
Lei LEI ; Jia-yu ZHAI ; Tian ZHOU ; Quan LIU ; Shuai-nan LIU ; Cai-na LI ; Hui CAO ; Cun-yu FENG ; Min WU ; Lei-lei CHEN ; Li-ran LEI ; Xuan PAN ; Zhan-zhu LIU ; Yi HUAN ; Zhu-fang SHEN
Acta Pharmaceutica Sinica 2024;59(10):2782-2790
G protein-coupled receptor (GPR) 40, as one of GPRs family, plays a potential role in regulating glucose and lipid metabolism. To study the effect of GPR40 novel agonist SZZ15-11 on hyperglycemia and hyperlipidemia and its potential mechanism, spontaneous type 2 diabetic KKAy mice, human hepatocellular carcinoma HepG2 cells and murine mature adipocyte 3T3-L1 cells were used. KKAy mice were divided into four groups, vehicle group, TAK group, SZZ (50 mg·kg-1) group and SZZ (100 mg·kg-1) group, with oral gavage of 0.5% sodium carboxymethylcellulose (CMC), 50 mg·kg-1 TAK875, 50 and 100 mg·kg-1 SZZ15-11 respectively for 45 days. Fasting blood glucose, blood triglyceride (TG) and total cholesterol (TC), non-fasting blood glucose were tested. Oral glucose tolerance test and insulin tolerance test were executed. Blood insulin and glucagon were measured
4.Surveillance of bacterial resistance in tertiary hospitals across China:results of CHINET Antimicrobial Resistance Surveillance Program in 2022
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Yanyan LIU ; Yong AN
Chinese Journal of Infection and Chemotherapy 2024;24(3):277-286
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5%were gram-positive and 70.5%were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3%,76.7%and 77.9%,respectively.Overall,94.0%of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8%of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2%in the isolates from children and 95.7%in the isolates from adults.The resistance rate to carbapenems was lower than 13.1%in most Enterobacterales species except for Klebsiella,21.7%-23.1%of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1%to 13.3%.The prevalence of meropenem-resistant strains decreased from 23.5%in 2019 to 18.0%in 2022 in Pseudomonas aeruginosa,and decreased from 79.0%in 2019 to 72.5%in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.
5.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
6.Antimicrobial resistance profile of clinical isolates in hospitals across China:report from the CHINET Antimicrobial Resistance Surveillance Program,2023
Yan GUO ; Fupin HU ; Demei ZHU ; Fu WANG ; Xiaofei JIANG ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Yuling XIAO ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Jingyong SUN ; Qing CHEN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yunmin XU ; Sufang GUO ; Yanyan WANG ; Lianhua WEI ; Keke LI ; Hong ZHANG ; Fen PAN ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Wei LI ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Qian SUN ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanqing ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hua FANG ; Penghui ZHANG ; Bixia YU ; Ping GONG ; Haixia SHI ; Kaizhen WEN ; Yirong ZHANG ; Xiuli YANG ; Yiqin ZHAO ; Longfeng LIAO ; Jinhua WU ; Hongqin GU ; Lin JIANG ; Meifang HU ; Wen HE ; Jiao FENG ; Lingling YOU ; Dongmei WANG ; Dong'e WANG ; Yanyan LIU ; Yong AN ; Wenhui HUANG ; Juan LI ; Quangui SHI ; Juan YANG ; Abulimiti REZIWAGULI ; Lili HUANG ; Xuejun SHAO ; Xiaoyan REN ; Dong LI ; Qun ZHANG ; Xue CHEN ; Rihai LI ; Jieli XU ; Kaijie GAO ; Lu XU ; Lin LIN ; Zhuo ZHANG ; Jianlong LIU ; Min FU ; Yinghui GUO ; Wenchao ZHANG ; Zengguo WANG ; Kai JIA ; Yun XIA ; Shan SUN ; Huimin YANG ; Yan MIAO ; Jianping WANG ; Mingming ZHOU ; Shihai ZHANG ; Hongjuan LIU ; Nan CHEN ; Chan LI ; Cunshan KOU ; Shunhong XUE ; Jilu SHEN ; Wanqi MEN ; Peng WANG ; Xiaowei ZHANG ; Xiaoyan ZENG ; Wen LI ; Yan GENG ; Zeshi LIU
Chinese Journal of Infection and Chemotherapy 2024;24(6):627-637
Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0% were gram-positive and 71.0% were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6%,81.9% and 78.5%,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9% of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4% of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1% in the isolates from children and and 95.9% in the isolates from adults.The resistance rate to carbapenems was lower than 15.0% for most Enterobacterales species except for Klebsiella,22.5% and 23.6% of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6% to 10.0%.The resistance rate to imipenem and meropenem was 21.9% and 17.4% for Pseudomonas aeruginosa,respectively,and 67.5% and 68.1% for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.
7.Recompensation of complications in patients with hepatitis B virus-related decompensated cirrhosis treated with entecavir antiviral therapy.
Ting ZHANG ; You DENG ; Hai Yan KANG ; Hui Ling XIANG ; Yue Min NAN ; Jin Hua HU ; Qing Hua MENG ; Ji Lian FANG ; Jie XU ; Xiao Ming WANG ; Hong ZHAO ; Calvin Q PAN ; Ji Dong JIA ; Xiao Yuan XU ; Wen XIE
Chinese Journal of Hepatology 2023;31(7):692-697
Objective: To analyze the occurrence of recompensation conditions in patients with chronic hepatitis B virus-related decompensated cirrhosis after entecavir antiviral therapy. Methods: Patients with hepatitis B virus-related decompensated cirrhosis with ascites as the initial manifestation were prospectively enrolled. Patients who received entecavir treatment for 120 weeks and were followed up every 24 weeks (including clinical endpoint events, hematological and imaging indicators, and others) were calculated for recompensation rates according to the Baveno VII criteria. Measurement data were compared using the Student t-test or Mann-Whitney U test between groups. Categorical data were compared by the χ (2) test or Fisher's exact probability method between groups. Results: 283 of the 320 enrolled cases completed the 120-week follow-up, and 92.2% (261/283) achieved a virological response (HBV DNA 20 IU/ml). Child-Pugh and MELD scores were significantly improved after treatment (8.33 ± 1.90 vs. 5.77 ± 1.37, t = 12.70, P < 0.001; 13.37 ± 4.44 vs. 10.45 ± 4.58, t = 5.963, P < 0.001). During the 120-week follow-up period, 14 cases died, two received liver transplants, 19 developed hepatocellular cancer, 11 developed gastroesophageal variceal bleeding, and four developed hepatic encephalopathy. 60.4% (171/283) (no decompensation events occurred for 12 months) and 56.2% (159/283) (no decompensation events occurred for 12 months and improved liver function) of the patients had achieved clinical recompensation within 120 weeks. Patients with baseline MELD scores > 15 after active antiviral therapy achieved higher recompensation than patients with baseline MELD scores ≤15 [50/74 (67.6%) vs. 109/209 (52.2%), χ (2) = 5.275, P = 0.029]. Conclusion: Antiviral therapy can significantly improve the prognosis of patients with hepatitis B virus-related decompensated cirrhosis. The majority of patients (56.2%) had achieved recompensation. Patients with severe disease did not have a lower probability of recompensation at baseline than other patients.
Humans
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Hepatitis B virus/genetics*
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Hepatitis B, Chronic/drug therapy*
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Antiviral Agents/adverse effects*
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Esophageal and Gastric Varices/complications*
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Liver Cirrhosis/complications*
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Treatment Outcome
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Gastrointestinal Hemorrhage/complications*
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Hepatitis B/drug therapy*
8.Interpretation and thinking of indicators of pharmaceutical administration in National Tertiary Public Hospitals Performance Evaluation Operational Manual (2022 edition)
Silu XU ; Nan WU ; Ning CAI ; Min ZHAO ; Jie PAN ; Jifu WEI
China Pharmacy 2022;33(13):1541-1547
OBJECTIVE To interpret the revision of the in dicators o f pharmaceutical administration in National Tertiary Public Hospitals Performance Evaluation Operational Manual (2022 edition)[hereinafter referred to as the Mannual(2022 edition)],and to provide reference for the implementation of a new round of performance appraisal in tertiary public hospitals. METHODS The contents and revision details of the indicators of pharmaceutical administration in the Mannual(2022 edition)were described briefly,and the revised contents were interpreted and relevant suggestions were put forward. RESULTS & CONCLUSIONS The Manual(2022 edition)continued the scope of performance evaluation ,indicators’structure and sequence in the Manual(2020 edition),which focused on rational drug use and drug cost control. The Manual (2022 edition) placed more emphasis on strengthening the provision and use of essential medicines and selected drugs in the centralized drug procurement ,and further reducing the burden of medical costs in patients. It is suggested that tertiary public hospitals scientifically set indicators for the use of essential medicines ,selected drugs in the centralized drug procurement ,auxiliary drugs and antibacterial drugs in clinical departments,and improve relevant incentive mechanisms and performance assessment systems ;strengthen the interpretation of policies about essential medicines and drug centralized procurement ,as well as the training of rational drug use ;optimize in-hospital drug catalog and formulary ;formulate medication standards ,strengthen prescription review ,rational medication review and assessment ;establish and improve the drug use monitoring and evaluation and early warning system so as to standardize clinical drug use behavior by information technology ;strengthen the use of essential drugs and centrally purchase selected drugs on the basis of ensuring rationality ;control the unreasonable gradually reduce the increase in average drug costs.
9.Related factors of urinary tract infections in inpatients based on real world data.
Chun Hong BIAN ; Yue PAN ; Ya Nan TAN ; Li Min ZHANG ; Rong Qi WANG ; Guo Jun ZHANG
Chinese Journal of Preventive Medicine 2022;56(11):1636-1641
To analyze the risk factors for urinary tract infection (UTI) among inpatients. The case data of 1 875 inpatients receiving urinary bacterial culture in Beijing Haidian Hospital from October 2019 to May 2021 were analyzed retrospectively. According to the etiological diagnostic criteria of UTI, they were divided into infection group and non-infection group. The species and distribution of pathogens in the infection group were analyzed, and the case data and laboratory indexes were subjected to univariate analysis. The variables with statistical significance were selected for binary logistic regression to analyze the risk factors of urinary tract infection and establish a prediction model. The receiver operating characteristic (ROC) curve was drawn for each parameter included in the model, and the area under the curve (AUC) was calculated. The diagnostic and predictive efficacy of each parameter alone and their combination for UTI were evaluated. So, a total of 1 162 patients with non-infection group and 713 patients with UTI were detected. Among the cultured pathogens, the constituent ratio of Gram-negative bacteria, Gram-positive bacteria and fungi was 57.2%(408/713), 35.9%(256/713) and 6.9%(49/713) respectively. Multivariate analysis showed that, Age, duration of urinary catheterization>7 d, stroke and orthopedic surgery were the risk factors of UTI among inpatients. The use of antibiotics is a protective factor for urinary tract infections. The prediction model of UTI was established by the risk factors, age, duration of urinary catheterization>7 d, stroke, orthopedic surgery, urinary leukocyte esterase, urinary nitrite and Coefficient of variability of red blood cell volume distribution width (RDW-CV). The AUC of the combination of the eight parameters in diagnosing and predicting UTI was 0.835 (95%CI: 0.816-0.855), with the sensitivity of 70.7% and the specificity of 82.8%. In conclusion,the combination of the eight parameters can better assist in the diagnosis and prediction of UTI, and provide an experimental basis for clinicians to judge UTI.
Humans
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Retrospective Studies
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Inpatients
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Urinary Tract Infections/microbiology*
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Urinalysis
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Stroke

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