What is it about?
ESBLs are rising among community-onset infections. It is only a matter of time until healthcare providers hike up carbapenem prescription rates when resistance to 3rd generation cephalosporins exceeds an arbitrary threshold.
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Why is it important?
The study derives and internally validates the ESBL Prediction Score that stratifies patients according to predicted risk of ESBLs based on clinical variables at initial presentation. This helps identify patients who may benefit the most from empirical carbapenem therapy from those who do not need carbapenems at all.
Perspectives
This is one of the simplest and most precise clinical tools for prediction of ESBLs. The scores includes only 3 variables and has high discrimination (area under receiver operating characteristic curve of 0.86 and negative-predictive value of 97-99%, depending on breakpoint used). In this paper, we present a proposed algorithm to assist healthcare providers utilize the ESBL Prediction Score. The algorithm categorizes patients into low, moderate and high risk of ESBLs and incorporates acute severity of illness into the decision-making process. In other words, the user's manual is included with this tool for convenience. You are very welcomed.
Prof. Majdi Al-Hasan
University of South Carolina School of Medicine
Read the Original
This page is a summary of: Clinical Risk Score for Prediction of Extended-Spectrum β-Lactamase–Producing Enterobacteriaceae in Bloodstream Isolates, Infection Control and Hospital Epidemiology, December 2016, Cambridge University Press,
DOI: 10.1017/ice.2016.292.
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