Literature DB >> 19162374

Waterlow score to predict patients at risk of developing Clostridium difficile-associated disease.

J Tanner1, D Khan, D Anthony, J Paton.   

Abstract

This study describes the development and testing of an assessment tool to predict the risk of patients developing Clostridium difficile-associated disease (CDAD). The three phases of the study include the development of the tool, prospective testing of the validity of the tool using 1468 patients in a medical assessment unit and external retrospective testing using data from 29 425 patients. In the first phase of the study, receiver operating characteristic (ROC) analysis identified the Waterlow assessment score as having the ability to predict CDAD (area under the curve: 0.827). The Waterlow tool was then tested prospectively with 1468 patients admitted to a medical assessment unit. A total of 1385 patients (94%) had a Waterlow score <20 and 83 patients (6%) had a Waterlow score of > or = 20. After a three-month follow-up, six patients in the low Waterlow score group developed CDAD (0.4%) and 14 patients in the high score group developed CDAD (17%). The sensitivity and specificity of the Waterlow score to predict the risk of developing CDAD were 70% and 95%, respectively. Similar results were obtained when the tool was tested retrospectively on a large external patient data set. The Waterlow score appears to predict patients' risk of developing CDAD and although it did not identify all cases, it highlighted a small group of patients who had a disproportionately large number of CDAD cases. The Waterlow score can be used to target patients most at risk of developing CDAD.

Entities:  

Mesh:

Year:  2009        PMID: 19162374     DOI: 10.1016/j.jhin.2008.11.017

Source DB:  PubMed          Journal:  J Hosp Infect        ISSN: 0195-6701            Impact factor:   3.926


  7 in total

1.  Waterlow score as a surrogate marker for predicting adverse outcome in acute pancreatitis.

Authors:  K Gillick; H Elbeltagi; S Bhattacharya
Journal:  Ann R Coll Surg Engl       Date:  2016-01       Impact factor: 1.891

2.  Development and validation of a Clostridium difficile infection risk prediction model.

Authors:  Erik R Dubberke; Yan Yan; Kimberly A Reske; Anne M Butler; Joshua Doherty; Victor Pham; Victoria J Fraser
Journal:  Infect Control Hosp Epidemiol       Date:  2011-04       Impact factor: 3.254

3.  Clostridium difficile-associated diarrhea in a tertiary care medical center.

Authors:  Marilee D Obritsch; Jeffrey S Stroup; Ryan M Carnahan; David N Scheck
Journal:  Proc (Bayl Univ Med Cent)       Date:  2010-10

4.  Estimating Local Costs Associated With Clostridium difficile Infection Using Machine Learning and Electronic Medical Records.

Authors:  Theodore R Pak; Kieran I Chacko; Timothy O'Donnell; Shirish S Huprikar; Harm van Bakel; Andrew Kasarskis; Erick R Scott
Journal:  Infect Control Hosp Epidemiol       Date:  2017-11-06       Impact factor: 3.254

5.  Predicting the Risk of Clostridium difficile Infection upon Admission: A Score to Identify Patients for Antimicrobial Stewardship Efforts.

Authors:  Jennifer L Kuntz; David H Smith; Amanda F Petrik; Xiuhai Yang; Micah L Thorp; Tracy Barton; Karen Barton; Matthew Labreche; Steven J Spindel; Eric S Johnson
Journal:  Perm J       Date:  2016

6.  Learning Data-Driven Patient Risk Stratification Models for Clostridium difficile.

Authors:  Jenna Wiens; Wayne N Campbell; Ella S Franklin; John V Guttag; Eric Horvitz
Journal:  Open Forum Infect Dis       Date:  2014-07-15       Impact factor: 3.835

7.  Toxigenic Clostridium difficile colonization among hospitalised adults; risk factors and impact on survival.

Authors:  Laura Behar; David Chadwick; Angela Dunne; Christopher I Jones; Claire Proctor; Chakravarthi Rajkumar; Paula Sharratt; Philip Stanley; Angela Whiley; Mark Wilks; Martin J Llewelyn
Journal:  J Infect       Date:  2017-04-21       Impact factor: 6.072

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.