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Wu TZ, Liang X, Li JQ, Li T, Yang LL, Li J, Xin JJ, Jiang J, Shi DY, Ren KK, Hao SR, Jin LF, Ye P, Huang JR, Xu XW, Gao ZL, Duan ZP, Han T, Wang YM, Wang BJ, Gan JH, Fen TT, Pan C, Chen YP, Huang Y, Xie Q, Lin SM, Chen X, Xin SJ, Li LJ, Li J. [Establishment of clinical features and prognostic scoring model in early-stage hepatitis B-related acute-on-chronic liver failure]. Zhonghua Gan Zang Bing Za Zhi 2020; 28:441-445. [PMID: 32403883 DOI: 10.3760/cma.j.cn501113-20200316-00116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Objective: To explore the clinical characteristics and establish a corresponding prognostic scoring model in patients with early-stage clinical features of hepatitis B-induced acute-on-chronic liver failure (HBV-ACLF). Methods: Clinical characteristics of 725 cases with hepatitis B-related acute-on-chronic hepatic dysfunction (HBV-ACHD) were retrospectively analyzed using Chinese group on the study of severe hepatitis B (COSSH). The independent risk factors associated with 90-day prognosis to establish a prognostic scoring model was analyzed by multivariate Cox regression, and was validated by 500 internal and 390 external HBV-ACHD patients. Results: Among 725 cases with HBV-ACHD, 76.8% were male, 96.8% had cirrhosis base,66.5% had complications of ascites, 4.1% had coagulation failure in respect to organ failure, and 9.2% had 90-day mortality rate. Multivariate Cox regression analysis showed that TBil, WBC and ALP were the best predictors of 90-day mortality rate in HBV-ACHD patients. The established scoring model was COSS-HACHADs = 0.75 × ln(WBC) + 0.57 × ln(TBil)-0.94 × ln(ALP) +10. The area under the receiver operating characteristic curve (AUROC) of subjects was significantly higher than MELD, MELD-Na, CTP and CLIF-C ADs(P < 0.05). An analysis of 500 and 390 cases of internal random selection group and external group had similar verified results. Conclusion: HBV-ACHD patients are a group of people with decompensated cirrhosis combined with small number of organ failure, and the 90-day mortality rate is 9.2%. COSSH-ACHDs have a higher predictive effect on HBV-ACHD patients' 90-day prognosis, and thus provide evidence-based medicine for early clinical diagnosis and treatment.
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Affiliation(s)
- T Z Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - X Liang
- Precision Medicine Center, Taizhou Central Hospital, Taizhou University Medical School, Taizhou 318000, China
| | - J Q Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - T Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - L L Yang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - J Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - J J Xin
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China; Precision Medicine Center, Taizhou Central Hospital, Taizhou University Medical School, Taizhou 318000, China
| | - J Jiang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China; Precision Medicine Center, Taizhou Central Hospital, Taizhou University Medical School, Taizhou 318000, China
| | - D Y Shi
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China; Precision Medicine Center, Taizhou Central Hospital, Taizhou University Medical School, Taizhou 318000, China
| | - K K Ren
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - S R Hao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - L F Jin
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - P Ye
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - J R Huang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - X W Xu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - Z L Gao
- Department of Liver and Infectious Disease, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510000, China
| | - Z P Duan
- Department of Liver and Infectious Diseases, Beijing YouAn Hospital, Capital Medical University, Beijing 100069, China
| | - T Han
- Department of Liver and Infectious Diseases, Tianjin Third Central Hospital, Tianjin 300170, China
| | - Y M Wang
- Department of Liver and Infectious Disease, The First Hospital Affiliated To AMU, Chongqing 400038, China
| | - B J Wang
- Department of Liver and Infectious Disease, Union Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430022, China
| | - J H Gan
- Department of Liver and Infectious Disease, The First Affilated Hospital of Soochow University, Suzhou 215006, China
| | - T T Fen
- Department of Liver and Infectious Disease, The First Affilated Hospital of Soochow University, Suzhou 215006, China
| | - C Pan
- Department of Liver and Infectious Diseases, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350005, China
| | - Y P Chen
- Department of Liver and Infectious Diseases, The First Affilated Hospital of Wenzhou Medical University, Wenzhou 325000, China
| | - Y Huang
- Department of Liver and Infectious Diseases, Xiangya Hospital Central South University, Changsha 410013, China
| | - Q Xie
- Department of Liver and Infectious Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China
| | - S M Lin
- Department of Liver and Infectious Diseases, First Affilated Hospital of Xi'an Jiaotong University, Xi'an 710061, China
| | - X Chen
- Institute of Pharmaceutical Biotechnology, Zhejiang University School of Medicine, Hangzhou 310058, China; Precision Medicine Center, Taizhou Central Hospital, Taizhou University Medical School, Taizhou 318000, China
| | - S J Xin
- Department of liver and Infectious Diseases, The Fifth Medical Center of PLA General Hospital, Beijing 100039, China
| | - L J Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
| | - J Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China; Precision Medicine Center, Taizhou Central Hospital, Taizhou University Medical School, Taizhou 318000, China
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Jackson N, Wu TZ, Adams-Sapper S, Satoorian T, Geisberg M, Murthy N, Lee L, Riley LW. A multiplexed, indirect enzyme-linked immunoassay for the detection and differentiation of E. coli from other Enterobacteriaceae and P. aeruginosa from other glucose non-fermenters. J Microbiol Methods 2019; 158:52-58. [PMID: 30708086 DOI: 10.1016/j.mimet.2019.01.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 01/19/2019] [Accepted: 01/28/2019] [Indexed: 10/27/2022]
Abstract
Gram-negative bacteria (GNB) are important causes of community (CA) and hospital (HA)- associated infections. Here we describe the development of an indirect ELISA (I-ELISA), which can be used to detect and differentiate the Enterobacteriaceae Escherichia coli, and glucose non-fermenter Pseudomonas aeruginosa from other GNB species. The I-ELISA utilizes six antibodies for bacterial speciation, which were grouped according to their bacterial targets; Enterobacteriaceae (SL-EntA and CH1810 mAb), Escherichia coli (SL-EcA and 6103-46 mAb), Pseudomonas aeruginosa (SL-PaA and SL-PaB). The six, anti-GNB antibodies were first screened against a panel of well-characterized clinical GNB isolates to optimize assay conditions and to determine individual antibody sensitivity and specificity. When tested against a diverse, blinded panel of 94 GNB clinical isolates, the I-ELISA exhibited the following sensitivity/specificity for each target: Enterobacteriaceae (94.4%/95%), E. coli (82.6%/88.7%), P. aeruginosa (83.3%/96%). An I-ELISA to detect and differentiate the most common GNB pathogens offers advantage in terms of simplicity over diagnostic tests currently used in most clinical settings.
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Affiliation(s)
- N Jackson
- School of Public Health, Division of Infectious Disease and Vaccinology, University of California, Berkeley, CA 94720, USA
| | - T Z Wu
- School of Public Health, Division of Infectious Disease and Vaccinology, University of California, Berkeley, CA 94720, USA
| | - S Adams-Sapper
- School of Public Health, Division of Infectious Disease and Vaccinology, University of California, Berkeley, CA 94720, USA
| | - T Satoorian
- Silver Lake Research Corporation, Azusa, CA 91702, USA
| | - M Geisberg
- Silver Lake Research Corporation, Azusa, CA 91702, USA
| | - N Murthy
- School of Public Health, Division of Infectious Disease and Vaccinology, University of California, Berkeley, CA 94720, USA
| | - L Lee
- School of Public Health, Division of Infectious Disease and Vaccinology, University of California, Berkeley, CA 94720, USA
| | - L W Riley
- School of Public Health, Division of Infectious Disease and Vaccinology, University of California, Berkeley, CA 94720, USA.
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