Literature DB >> 22205541

Risk stratification of spontaneous bacterial peritonitis in cirrhosis with ascites based on classification and regression tree analysis.

Ke-Qing Shi1, Yu-Chen Fan, Li Ying, Xian-Feng Lin, Mei Song, Ling-Fei Li, Xie-Yan Yu, Yong-Ping Chen, Ming-Hua Zheng.   

Abstract

Risk stratification for spontaneous bacterial peritonitis (SBP) in patients with cirrhosis and ascites helps guide care. Existing prediction models, such as end-stage liver disease (MELD) score, are accurate but controversial in clinical practice. We developed and validated a practical user-friendly bedside tool for SBP risk stratification of patients with cirrhosis and ascites. Using classification and regression tree (CART) analysis, a model was developed for prediction of SBP in cirrhosis with ascites. The CART model was derived on data collected from 676 patients admitted from January 2007 to December 2009 retrospectively, and then was prospectively tested in another independent 198 inpatients between January 2010 and December 2010. The accuracy of CART model was evaluated using the area under the receiver operating characteristic curve. The performance of the model was further validated by comparing its predictive accuracy with that of the MELD score. Furthermore, the model was used to stratify SBP among patients with MELD scores under 15. CART analysis identified four variables for prediction of SBP: creatinine, total bilirubin, prothrombin time and white blood cell count, and three risk groups: low (2.0%), intermediate (27.5-33.3%) and high (60.6-86.4%) risk. The accuracy of CART model (0.881) exceeded that of MELD (0.791). Subjects in the intermediate risk and high risk groups had 22.21-fold (95% confident interval (CI), 9.98-49.45) and 173.50-fold (95% CI, 77.68-634.33) increased risk of SBP, respectively, comparing with the low risk group. Similar results were found when this risk stratification was applied to the validation cohort. Cirrhotic patients with ascites at low, intermediate, and high risk for SBP can be easily identified using CART model, which provides clinicians with a validated, practical bedside tool for SBP risk stratification.

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Year:  2011        PMID: 22205541     DOI: 10.1007/s11033-011-1432-8

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.316


  21 in total

Review 1.  EASL clinical practice guidelines on the management of ascites, spontaneous bacterial peritonitis, and hepatorenal syndrome in cirrhosis.

Authors: 
Journal:  J Hepatol       Date:  2010-06-01       Impact factor: 25.083

2.  Management of adult patients with ascites due to cirrhosis: an update.

Authors:  Bruce A Runyon
Journal:  Hepatology       Date:  2009-06       Impact factor: 17.425

3.  The early prediction of mortality in acute pancreatitis: a large population-based study.

Authors:  B U Wu; R S Johannes; X Sun; Y Tabak; D L Conwell; P A Banks
Journal:  Gut       Date:  2008-06-02       Impact factor: 23.059

4.  Renal failure and bacterial infections in patients with cirrhosis: epidemiology and clinical features.

Authors:  Silvano Fasolato; Paolo Angeli; Lucia Dallagnese; Giulio Maresio; Erika Zola; Elena Mazza; Freddy Salinas; Silvio Donà; Stefano Fagiuoli; Antonietta Sticca; Giacomo Zanus; Umberto Cillo; Ilaria Frasson; Carla Destro; Angelo Gatta
Journal:  Hepatology       Date:  2007-01       Impact factor: 17.425

5.  Bacterial infections in cirrhosis: epidemiological changes with invasive procedures and norfloxacin prophylaxis.

Authors:  Javier Fernández; Miquel Navasa; Juliá Gómez; Jordi Colmenero; Jordi Vila; Vicente Arroyo; Juan Rodés
Journal:  Hepatology       Date:  2002-01       Impact factor: 17.425

6.  Pretreatment prediction of response to peginterferon plus ribavirin therapy in genotype 1 chronic hepatitis C using data mining analysis.

Authors:  Masayuki Kurosaki; Naoya Sakamoto; Manabu Iwasaki; Minoru Sakamoto; Yoshiyuki Suzuki; Naoki Hiramatsu; Fuminaka Sugauchi; Hiroshi Yatsuhashi; Namiki Izumi
Journal:  J Gastroenterol       Date:  2010-09-10       Impact factor: 7.527

7.  Ascites: aetiology, mortality and the prevalence of spontaneous bacterial peritonitis.

Authors:  Jahangir Khan; Pekka Pikkarainen; Anna-Liisa Karvonen; Tuula Mäkelä; Markku Peräaho; Eeva Pehkonen; Pekka Collin
Journal:  Scand J Gastroenterol       Date:  2009       Impact factor: 2.423

8.  Predicting early mortality after acute variceal hemorrhage based on classification and regression tree analysis.

Authors:  Salvador Augustin; Laura Muntaner; José T Altamirano; Antonio González; Esteban Saperas; Joan Dot; Monder Abu-Suboh; Josep R Armengol; Joan R Malagelada; Rafael Esteban; Jaime Guardia; Joan Genescà
Journal:  Clin Gastroenterol Hepatol       Date:  2009-08-21       Impact factor: 11.382

9.  Primary prophylaxis of spontaneous bacterial peritonitis delays hepatorenal syndrome and improves survival in cirrhosis.

Authors:  Javier Fernández; Miquel Navasa; Ramón Planas; Silvia Montoliu; David Monfort; German Soriano; Carmen Vila; Alberto Pardo; Enrique Quintero; Victor Vargas; Jose Such; Pere Ginès; Vicente Arroyo
Journal:  Gastroenterology       Date:  2007-07-03       Impact factor: 22.682

10.  Role of fluoroquinolones in the primary prophylaxis of spontaneous bacterial peritonitis: meta-analysis.

Authors:  Rohit Loomba; Robert Wesley; Andrew Bain; Gyorgy Csako; Frank Pucino
Journal:  Clin Gastroenterol Hepatol       Date:  2008-12-27       Impact factor: 11.382

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  4 in total

1.  Using Classification and Regression Trees (CART) to Identify Prescribing Thresholds for Cardiovascular Disease.

Authors:  Chris Schilling; Duncan Mortimer; Kim Dalziel; Emma Heeley; John Chalmers; Philip Clarke
Journal:  Pharmacoeconomics       Date:  2016-02       Impact factor: 4.981

2.  Predictors of spontaneous bacterial peritonitis in Romanian adults with liver cirrhosis: Focus on the neutrophil-to-lymphocyte ratio.

Authors:  Roxana-Emanuela Popoiag; Andra-Iulia Suceveanu; Adrian-Paul Suceveanu; Sergiu Ioan Micu; Felix Voinea; Laura Mazilu; Lucian Cristian Petcu; Eugenia Panaitescu; Georgeta Cozaru; Carmen Fierbințeanu-Braticevici
Journal:  Exp Ther Med       Date:  2021-07-12       Impact factor: 2.447

3.  Explainable machine learning model for predicting spontaneous bacterial peritonitis in cirrhotic patients with ascites.

Authors:  Yingying Hu; Ruijia Chen; Haibing Gao; Haitao Lin; Jinye Wang; Xiaowei Wang; Jingfeng Liu; Yongyi Zeng
Journal:  Sci Rep       Date:  2021-11-04       Impact factor: 4.379

Review 4.  Emergency Management of Spontaneous Bacterial Peritonitis - A Clinical Review.

Authors:  Tracy MacIntosh
Journal:  Cureus       Date:  2018-03-01
  4 in total

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