Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-14T04:30:52.137Z Has data issue: false hasContentIssue false

A Clinical Prediction Rule for Fluoroquinolone Resistance in Healthcare-Acquired Gram-Negative Urinary Tract Infection

Published online by Cambridge University Press:  02 January 2015

Pinyo Rattanaumpawan
Affiliation:
Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania
Pam Tolomeo
Affiliation:
Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania
Warren B. Bilker
Affiliation:
Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania Center for Education and Research on Therapeutics and University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania
Ebbing Lautenbach*
Affiliation:
Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania Center for Education and Research on Therapeutics and University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania Division of Infectious Diseases of the Department of Medicine, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania.
*
University of Pennsylvania School of Medicine, Center for Clinical Epidemiology and Biostatistics, 825 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021 (ebbing@mail.med.upenn.edu)

Abstract

Data from a case-control study were used to derive and internally validate a prediction rule for identifying fluoroquinolone resistance in healthcare-acquired gram-negative urinary tract infection. This prediction rule has an excellent sensitivity and specificity (C-statistic, 0.816). External validation is necessary before implementing this rule to optimize empirical antibiotic use in clinical practice.

Type
Concise Communications
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Lautenbach, E, Polk, RE. Resistant gram-negative bacilli: a neglected healthcare crisis? Am J Health Syst Pharm 2007;64:S3S21.Google Scholar
2.Bantar, C, Sartori, B, Vesco, E, et al. A hospitalwide intervention program to optimize the quality of antibiotic use: impact on prescribing practice, antibiotic consumption, cost savings, and bacterial resistance. Clin Infect Dis 2003;37:180186.Google Scholar
3.Garner, JS, Jarvis, WR, Emori, TG, Horan, TC, Hughes, JM. CDC definitions for nosocomial infections, 1988. Am J Infect Control 1988;16:128140.Google Scholar
4.Clinical and Laboratory Standards Institute (CLSI). Performance Standards for Antimicrobial susceptibility Testing: 18th Informational Supplement. Wayne, PA: CLSI, 2008. CLSI document. M100-S18.Google Scholar
5.Efron, B, Tibshirani, RJ. An Introduction to the Bootstrap. London: Chapman & Hall, 1993.Google Scholar
6.Rattanaumpawan, P, Tolomeo, P, Bilker, WB, Fishman, NO, Lautenbach, E. Risk factors for fluoroquinolone resistance in gram-negative bacilli causing healthcare-acquired urinary tract infections. J Hosp Infect 2010;76:324327.CrossRefGoogle ScholarPubMed
7.Dellit, TH, Owens, RC, McGowan, JE, et al. Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America guidelines for developing an institutional program to enhance antimicrobial stewardship. Clin Infect Dis 2007;44: 159177.Google Scholar