Literature DB >> 21722666

A simple model to predict bacteremia in women with acute pyelonephritis.

Kyung Su Kim1, Kyuseok Kim, You Hwan Jo, Tae Yun Kim, Jin Hee Lee, Se Jong Lee, Joong Eui Rhee, Gil Joon Suh.   

Abstract

OBJECTIVES: To construct a simple model to predict bacteremia in women with uncomplicated acute pyelonephritis (APN) for the judicious use of blood cultures.
METHODS: A prospective database including 735 women with uncomplicated APN at an academic urban emergency department was analyzed retrospectively. Independent risk factors were determined using multivariate logistic regression in two-thirds of patients. Cutoff values representing 10% and 30% of risk were selected for the stratification. This model was internally and externally validated using a remaining one-thirds of patients and 169 independent patients, respectively.
RESULTS: Independent risk factors were as follows: age ≥65 years (odds ratio [OR]=5.18, 4 points), vomiting (OR=2.40, 2 points), heart rate >110 beats/min (OR=2.35, 2 points), segmented neutrophils >90% (OR=3.17, 3 points), and urine WBC ≥50/HPF (OR=4.27, 4 points). Patients were stratified as low (points <4), intermediate (points, 4-6), or high risk (7≤ points). The areas under receiver operating characteristics curves were 0.707 and 0.792 in internal and external validation cohorts, respectively. The model stratified internal and external validation cohort into low (8.5% and 5.7%), intermediate (16.5% and 14.8%), and high risk of bacteremia (42.0% and 56.4%).
CONCLUSIONS: This model provides a useful tool to predict the risk of bacteremia, which can be helpful to decide whether to perform blood cultures and whether to admit the patient for the intravenous antibiotics in women with uncomplicated APN.
Copyright © 2011 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21722666     DOI: 10.1016/j.jinf.2011.06.007

Source DB:  PubMed          Journal:  J Infect        ISSN: 0163-4453            Impact factor:   6.072


  11 in total

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