Developing a model to estimate the probability of bacteremia in women with community-onset febrile urinary tract infection

  • Won Sup Oh Kangwon National University School of Medicine, Chuncheon, Korea
  • Yeon-Sook Kim Chungnam National University School of Medicine, Daejeon, Korea
  • Joon Sup Yeom Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
  • Hee Kyoung Choi Wonju Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Korea
  • Yee Gyung Kwak Inje University Ilsan-Paik Hospital, Goyang, Korea
  • Jae-Bum Jun Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea
  • Seong Yeon Park Ilsan Hospital, Dongguk University College of Medicine, Koyang, Korea
  • Jin-Won Chung Jung-Ang University College of Medicine, Seoul, Korea
  • Ji-Young Rhee Dankook University Medical College, Cheonan, Korea
  • Baek-Nam Kim Inje University Sanggye-Paik Hospital, Seoul, Korea
Keywords: urinary tract infection, pyelonephritis, bacteremia, decision support technique, sensitivity, specificity

Abstract

Introduction: Among patients with urinary tract infection (UTI), bacteremic cases show higher mortality rates than do nonbacteremic cases. Early identification of bacteremic cases is crucial for severity assessment of patients with febrile UTI. This study aimed to identify predictors associated with bacteremia in women with community-onset febrile UTI and to develop a prediction model to estimate the probability of bacteremic cases.

Methodology: This cross-sectional study included women consecutively hospitalized with community-onset febrile UTI at 10 hospitals in Korea. Multiple logistic regression identified predictors associated with bacteremia among candidate variables chosen from univariate analysis. A prediction model was developed using all predictors weighted by their regression coefficients.

Results: From July to September 2014, 383 women with febrile UTI were included: 115 (30.0%) bacteremic and 268 (70.0%) nonbacteremic cases. A prediction model consisted of diabetes mellitus (1 point), urinary tract obstruction by stone (2), costovertebral angle tenderness (2), a fraction of segmented neutrophils of > 90% (2), thrombocytopenia (2), azotemia (2), and the fulfillment of all criteria for systemic inflammatory response syndrome (2). The c statistic for the model was 0.807 (95% confidence interval [CI], 0.757–0.856). At a cutoff value of ≥ 3, the model had a sensitivity of 86.1% (95% CI, 78.1–91.6%) and a specificity of 54.9% (95% CI, 48.7–91.6%).

Conclusions: Our model showed a good discriminatory power for early identification of bacteremic cases in women with community-onset febrile UTI. In addition, our model can be used to identify patients at low risk for bacteremia because of its relatively high sensitivity.

Author Biographies

Won Sup Oh, Kangwon National University School of Medicine, Chuncheon, Korea
Department of Internal Medicine
Yeon-Sook Kim, Chungnam National University School of Medicine, Daejeon, Korea
Department of Internal Medicine
Joon Sup Yeom, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
Department of Internal Medicine
Hee Kyoung Choi, Wonju Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Korea
Department of Internal Medicine
Yee Gyung Kwak, Inje University Ilsan-Paik Hospital, Goyang, Korea
Department of Internal Medicine
Jae-Bum Jun, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan, Korea
Department of Internal Medicine
Seong Yeon Park, Ilsan Hospital, Dongguk University College of Medicine, Koyang, Korea
Department of Internal Medicine
Jin-Won Chung, Jung-Ang University College of Medicine, Seoul, Korea
Department of Internal Medicine
Ji-Young Rhee, Dankook University Medical College, Cheonan, Korea
Department of Internal Medicine
Baek-Nam Kim, Inje University Sanggye-Paik Hospital, Seoul, Korea
Department of Internal Medicine
Published
2016-11-24
How to Cite
1.
Oh WS, Kim Y-S, Yeom JS, Choi HK, Kwak YG, Jun J-B, Park SY, Chung J-W, Rhee J-Y, Kim B-N (2016) Developing a model to estimate the probability of bacteremia in women with community-onset febrile urinary tract infection. J Infect Dev Ctries 10:1222-1229. doi: 10.3855/jidc.7559
Section
Original Articles