1.Effect of Zhigancao Decoction compared with Zhenwu Decoction on hemodynamics, serum MMP-9 , TIMP-1 and myocardial enzymesin in aged patients with chronic heart failure
Chinese Journal of Biochemical Pharmaceutics 2015;35(10):61-64
Objective To compare the effect of Zhigancao Decoction and Zhenwu Decoction on hemodynamics, matrix metalloproteinase-9 (MMP-9), tissue inhibitor of metalloproteinase-1 (TIMP-1) and myocardial enzyme of elderly patients with chronic heart failure.Methods 40 elderly patients with chronic heart failure in the first affiliated hospital of the medical college, Shihezi university were selected and randomly divided into Zhigancao Decoction group (n=20) and Zhenwu Decoction group (n =20) .The both of two groups were given conventional treatment, then were treated with respective drug according to different groups with two courses, one course of two weeks.The hemodynamic, MMP-9, TIMP-1 and myocardial enzyme spectrum indexes of two groups were compared post-treatment.Results After treatment, the indexes of hemodynamics in two groups were improved, hemodynamic indexes of Zhigancao Decoction recovered better than those of Zhenwu Decoction (P<0.05) .The serum MMP-9, MMP-9/TIMP-1 of Zhigancao Decoction group were lower and TIMP-1 was higher than those of Zhenwu Decoction group (P<0.05).The myocardial enzyme indexes in both groups were lower post-treatment, and the above indexes in Zhigancao Decoction were lower than those in Zhenwu Decoction group (P<0.05) . Conclusion Zhigancao Decoction could obviously improve the symptoms of chronic heart failure in elderly patients, which has the guiding significant in the clinical treatment.
2.Value of a risk assessment model in predicting venous thromboembolism in patients with liver failure after artificial liver support therapy
Sufang LU ; Rui HUANG ; Hongli ZHAO ; Dandan WANG ; Yuzhen DING ; Hong ZHOU
Journal of Clinical Hepatology 2023;39(3):613-619
Objective To investigate the value of a risk assessment model in predicting venous thromboembolism (VTE) in patients with liver failure after artificial liver support therapy. Methods A retrospective analysis was performed for the clinical data of 124 patients with liver failure who received artificial liver support therapy in Affiliated Drum Tower Hospital of Nanjing University Medical School from March 2019 to December 2021, among whom there were 41 patients with VTE (observation group) and 143 patients without VTE (control group). Related clinical data were compared between the two groups, and the Caprini risk assessment model was used for scoring and risk classification of the patients in both groups. The t -test was used for comparison of continuous data between two groups; the chi-square test was used for comparison of categorical data between two groups; the Mann-Whitney U rank sum test was used for comparison of ranked data between two groups. The logistic regression analysis was used to investigate the independent risk factors for VTE in patients with liver failure after artificial liver support therapy. The receiver operating characteristic (ROC) curve was used to investigate the value of Caprini score and the multivariate predictive model used alone or in combination in predicting VTE. Results The observation group had a significantly higher Caprini score than the control group (4.39±1.10 vs 3.12±1.04, t =6.805, P < 0.001). There was a significant difference between the two groups in risk classification based on Caprini scale ( P < 0.05), and the patients with high risk or extremely high risk accounted for a higher proportion among the patients with VTE. The univariate analysis showed that there were significant differences between the two groups in age ( t =6.400, P < 0.001), catheterization method ( χ 2 =14.413, P < 0.001), number of times of artificial liver support therapy ( Z =-4.720, P < 0.001), activity ( Z =-6.282, P < 0.001), infection ( χ 2 =33.071, P < 0.001), D-dimer ( t =8.746, P < 0.001), 28-day mortality rate ( χ 2 =5.524, P =0.022). The multivariate analysis showed that number of times of artificial liver support therapy (X 1 ) (odds ratio [ OR ]=0.251, 95% confidence interval [ CI ]: 0.111-0.566, P =0.001), activity (X 2 ) ( OR =0.122, 95% CI : 0.056-0.264, P < 0.001), D-dimer (X 3 ) ( OR =2.921, 95% CI : 1.114-7.662, P =0.029) were independent risk factors for VTE in patients with liver failure after artificial liver support therapy. The equation for individual predicted probability was P =1/[1+e -(7.425-1.384X 1 -2.103X 2 +1.072X 3 ) ]. The ROC curve analysis showed that Caprini score had an area under the ROC curve of 0.802 (95% CI : 0.721-0.882, P < 0.001), and the multivariate model had an area under the ROC curve of 0.768 (95% CI : 0.685-0.851, P < 0.001), while the combination of Caprini score and the multivariate model had an area under the ROC curve of 0.957 (95% CI : 0.930-0.984, P < 0.001). Conclusion The Caprini risk assessment model has a high predictive efficiency for the risk of VTE in patients with liver failure after artificial liver support therapy, and its combination with the multivariate predictive model can significantly improve the prediction of VTE.
3.Changing resistance profiles of Enterobacter isolates in hospitals across China:results from the CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Shaozhen YAN ; Ziyong SUN ; Zhongju CHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yi XIE ; Mei KANG ; Fengbo ZHANG ; Ping JI ; Zhidong HU ; Jin LI ; Sufang GUO ; Han SHEN ; Wanqing ZHOU ; Yingchun XU ; Xiaojiang ZHANG ; Xuesong XU ; Chao YAN ; Chuanqing WANG ; Pan FU ; Wei JIA ; Gang LI ; Yuanhong XU ; Ying HUANG ; Dawen GUO ; Jinying ZHAO ; Wen'en LIU ; Yanming LI ; Hua YU ; Xiangning HUANG ; Bin SHAN ; Yan DU ; Shanmei WANG ; Yafei CHU ; Yuxing NI ; Jingyong SUN ; Yunsong YU ; Jie LIN ; Chao ZHUO ; Danhong SU ; Lianhua WEI ; Fengmei ZOU ; Yan JIN ; Chunhong SHAO ; Jihong LI ; Lixia ZHANG ; Juan MA ; Yunzhuo CHU ; Sufei TIAN ; Jinju DUAN ; Jianbang KANG ; Ruizhong WANG ; Hua FANG ; Fangfang HU ; Yunjian HU ; Xiaoman AI ; Fang DONG ; Zhiyong LÜ ; Hong ZHANG ; Chun WANG ; Yong ZHAO ; Ping GONG ; Lei ZHU ; Jinhua MENG ; Xiaobo MA ; Yanping ZHENG ; Jinsong WU ; Yuemei LU ; Ruyi GUO ; Yan ZHU ; Kaizhen WEN ; Yirong ZHANG ; Chunlei YUE ; Jiangshan LIU ; Wenhui HUANG ; Shunhong XUE ; Xuefei HU ; Hongqin GU ; Jiao FENG ; Shuping ZHOU ; Yan ZHOU ; Yunsheng CHEN ; Qing MENG ; Bixia YU ; Jilu SHEN ; Rui DOU ; Shifu WANG ; Wen HE ; Longfeng LIAO ; Lin JIANG
Chinese Journal of Infection and Chemotherapy 2024;24(3):309-317
Objective To examine the changing antimicrobial resistance profile of Enterobacter spp.isolates in 53 hospitals across China from 2015 t0 2021.Methods The clinical isolates of Enterobacter spp.were collected from 53 hospitals across China during 2015-2021 and tested for antimicrobial susceptibility using Kirby-Bauer method or automated testing systems according to the CHINET unified protocol.The results were interpreted according to the breakpoints issued by the Clinical & Laboratory Standards Institute(CLSI)in 2021(M100 31st edition)and analyzed with WHONET 5.6 software.Results A total of 37 966 Enterobacter strains were isolated from 2015 to 2021.The proportion of Enterobacter isolates among all clinical isolates showed a fluctuating trend over the 7-year period,overall 2.5%in all clinical isolates amd 5.7%in Enterobacterale strains.The most frequently isolated Enterobacter species was Enterobacter cloacae,accounting for 93.7%(35 571/37 966).The strains were mainly isolated from respiratory specimens(44.4±4.6)%,followed by secretions/pus(16.4±2.3)%and urine(16.0±0.9)%.The strains from respiratory samples decreased slightly,while those from sterile body fluids increased over the 7-year period.The Enterobacter strains were mainly isolated from inpatients(92.9%),and only(7.1±0.8)%of the strains were isolated from outpatients and emergency patients.The patients in surgical wards contributed the highest number of isolates(24.4±2.9)%compared to the inpatients in any other departement.Overall,≤ 7.9%of the E.cloacae strains were resistant to amikacin,tigecycline,polymyxin B,imipenem or meropenem,while ≤5.6%of the Enterobacter asburiae strains were resistant to these antimicrobial agents.E.asburiae showed higher resistance rate to polymyxin B than E.cloacae(19.7%vs 3.9%).Overall,≤8.1%of the Enterobacter gergoviae strains were resistant to tigecycline,amikacin,meropenem,or imipenem,while 10.5%of these strains were resistant to polycolistin B.The overall prevalence of carbapenem-resistant Enterobacter was 10.0%over the 7-year period,but showing an upward trend.The resistance profiles of Enterobacter isolates varied with the department from which they were isolated and whether the patient is an adult or a child.The prevalence of carbapenem-resistant E.cloacae was the highest in the E.cloacae isolates from ICU patients.Conclusions The results of the CHINET Antimicrobial Resistance Surveillance Program indicate that the proportion of Enterobacter strains in all clinical isolates fluctuates slightly over the 7-year period from 2015 to 2021.The Enterobacter strains showed increasing resistance to multiple antimicrobial drugs,especially carbapenems over the 7-year period.