Developing a model to estimate the probability of bacteremia in women with community-onset febrile urinary tract infection
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...
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
The Journal of Infection in Developing Countries
2016-11-01
|
| Series: | Journal of Infection in Developing Countries |
| Subjects: | |
| Online Access: | https://jidc.org/index.php/journal/article/view/7559 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850193651215368192 |
|---|---|
| author | Won Sup Oh Yeon-Sook Kim Joon Sup Yeom Hee Kyoung Choi Yee Gyung Kwak Jae-Bum Jun Seong Yeon Park Jin-Won Chung Ji-Young Rhee Baek-Nam Kim |
| author_facet | Won Sup Oh Yeon-Sook Kim Joon Sup Yeom Hee Kyoung Choi Yee Gyung Kwak Jae-Bum Jun Seong Yeon Park Jin-Won Chung Ji-Young Rhee Baek-Nam Kim |
| author_sort | Won Sup Oh |
| collection | DOAJ |
| description | 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.
|
| format | Article |
| id | doaj-art-fb89fd60f36b43a7a2cec4b5caf80e47 |
| institution | OA Journals |
| issn | 1972-2680 |
| language | English |
| publishDate | 2016-11-01 |
| publisher | The Journal of Infection in Developing Countries |
| record_format | Article |
| series | Journal of Infection in Developing Countries |
| spelling | doaj-art-fb89fd60f36b43a7a2cec4b5caf80e472025-08-20T02:14:14ZengThe Journal of Infection in Developing CountriesJournal of Infection in Developing Countries1972-26802016-11-01101110.3855/jidc.7559Developing a model to estimate the probability of bacteremia in women with community-onset febrile urinary tract infectionWon Sup Oh0Yeon-Sook Kim1Joon Sup Yeom2Hee Kyoung Choi3Yee Gyung Kwak4Jae-Bum Jun5Seong Yeon Park6Jin-Won Chung7Ji-Young Rhee8Baek-Nam Kim9Kangwon National University School of Medicine, Chuncheon, KoreaChungnam National University School of Medicine, Daejeon, KoreaKangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, KoreaWonju Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, KoreaInje University Ilsan-Paik Hospital, Goyang, KoreaUlsan University Hospital, University of Ulsan College of Medicine, Ulsan, KoreaIlsan Hospital, Dongguk University College of Medicine, Koyang, KoreaJung-Ang University College of Medicine, Seoul, KoreaDankook University Medical College, Cheonan, KoreaInje University Sanggye-Paik Hospital, Seoul, KoreaIntroduction: 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. https://jidc.org/index.php/journal/article/view/7559urinary tract infectionpyelonephritisbacteremiadecision support techniquesensitivityspecificity |
| spellingShingle | Won Sup Oh Yeon-Sook Kim Joon Sup Yeom Hee Kyoung Choi Yee Gyung Kwak Jae-Bum Jun Seong Yeon Park Jin-Won Chung Ji-Young Rhee Baek-Nam Kim Developing a model to estimate the probability of bacteremia in women with community-onset febrile urinary tract infection Journal of Infection in Developing Countries urinary tract infection pyelonephritis bacteremia decision support technique sensitivity specificity |
| title | Developing a model to estimate the probability of bacteremia in women with community-onset febrile urinary tract infection |
| title_full | Developing a model to estimate the probability of bacteremia in women with community-onset febrile urinary tract infection |
| title_fullStr | Developing a model to estimate the probability of bacteremia in women with community-onset febrile urinary tract infection |
| title_full_unstemmed | Developing a model to estimate the probability of bacteremia in women with community-onset febrile urinary tract infection |
| title_short | Developing a model to estimate the probability of bacteremia in women with community-onset febrile urinary tract infection |
| title_sort | developing a model to estimate the probability of bacteremia in women with community onset febrile urinary tract infection |
| topic | urinary tract infection pyelonephritis bacteremia decision support technique sensitivity specificity |
| url | https://jidc.org/index.php/journal/article/view/7559 |
| work_keys_str_mv | AT wonsupoh developingamodeltoestimatetheprobabilityofbacteremiainwomenwithcommunityonsetfebrileurinarytractinfection AT yeonsookkim developingamodeltoestimatetheprobabilityofbacteremiainwomenwithcommunityonsetfebrileurinarytractinfection AT joonsupyeom developingamodeltoestimatetheprobabilityofbacteremiainwomenwithcommunityonsetfebrileurinarytractinfection AT heekyoungchoi developingamodeltoestimatetheprobabilityofbacteremiainwomenwithcommunityonsetfebrileurinarytractinfection AT yeegyungkwak developingamodeltoestimatetheprobabilityofbacteremiainwomenwithcommunityonsetfebrileurinarytractinfection AT jaebumjun developingamodeltoestimatetheprobabilityofbacteremiainwomenwithcommunityonsetfebrileurinarytractinfection AT seongyeonpark developingamodeltoestimatetheprobabilityofbacteremiainwomenwithcommunityonsetfebrileurinarytractinfection AT jinwonchung developingamodeltoestimatetheprobabilityofbacteremiainwomenwithcommunityonsetfebrileurinarytractinfection AT jiyoungrhee developingamodeltoestimatetheprobabilityofbacteremiainwomenwithcommunityonsetfebrileurinarytractinfection AT baeknamkim developingamodeltoestimatetheprobabilityofbacteremiainwomenwithcommunityonsetfebrileurinarytractinfection |