Literature DB >> 34040098

Clinical characteristics and prediction analysis of pediatric urinary tract infections caused by gram-positive bacteria.

Yu-Lung Hsu1, Shih-Ni Chang2, Che-Chen Lin2, Hsiao-Chuan Lin1, Huan-Cheng Lai1, Chin-Chi Kuo2,3,4, Kao-Pin Hwang1, Hsiu-Yin Chiang5.   

Abstract

Gram-positive (GP) pathogens are less accounted for in pediatric urinary tract infection (UTI), and their clinical impact is underrecognized. This study aimed to identify predictors of GP uropathogens in pediatric UTI. In this 14-year retrospective cohort of pediatric patients with UTI, we classified first-time UTIs cases into those caused by GP or Gram-negative (GN) bacteria. We constructed a multivariable logistic regression model to predict GP UTI. We evaluated model performance through calibration and discrimination plots. We developed a nomogram to predict GP UTI that is clinically feasible. Of 3783 children with first-time UTI, 166 (4.4%) were infected by GP and 3617 (95.6%) by GN bacteria. Among children with GP UTI, the most common uropathogens were vancomycin-resistant Enterococcus faecalis (VRE) (27.1%), Staphylococcus saprophyticus (26.5%), and coagulase-negative Staphylococci (12.7%). Eight independent risk factors were associated with GP UTI: Age ≥ 24 months (odds ratio [OR]: 3.21), no prior antibiotic use (OR: 3.13), serum white blood cell (WBC) count < 14.4 × 103/μL (OR: 2.19), high sensitivity C-reactive protein (hsCRP) < 3.4 mg/dL (OR: 2.18), hemoglobin ≥ 11.3 g/dL (OR: 1.90), negative urine leukocyte esterase (OR: 3.19), negative urine nitrite (OR: 4.13), and urine WBC < 420/μL (OR: 2.37). The model exhibited good discrimination (C-statistic 0.879; 95% CI 0.845-0.913) and calibration performance. VR E. faecalis, the leading GP uropathogen causing pediatric UTI, requires early detection for infection control. Our model for predicting GP UTI can help clinicians detect GP uropathogens and administer antibiotic regimen early.

Entities:  

Year:  2021        PMID: 34040098     DOI: 10.1038/s41598-021-90535-6

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  19 in total

1.  Association Between Uropathogen and Pyuria.

Authors:  Nader Shaikh; Timothy R Shope; Alejandro Hoberman; Alyssa Vigliotti; Marcia Kurs-Lasky; Judith M Martin
Journal:  Pediatrics       Date:  2016-06-21       Impact factor: 7.124

2.  Validation and Comparison of the 2003 and 2016 Diastolic Functional Assessments for Cardiovascular Mortality in a Large Single-Center Cohort.

Authors:  Hsin-Yueh Liang; Yen-Chun Lo; Hsiu-Yin Chiang; Ming-Fong Chen; Chin-Chi Kuo
Journal:  J Am Soc Echocardiogr       Date:  2020-02-20       Impact factor: 5.251

3.  Discrimination and Calibration of Clinical Prediction Models: Users' Guides to the Medical Literature.

Authors:  Ana Carolina Alba; Thomas Agoritsas; Michael Walsh; Steven Hanna; Alfonso Iorio; P J Devereaux; Thomas McGinn; Gordon Guyatt
Journal:  JAMA       Date:  2017-10-10       Impact factor: 56.272

Review 4.  Urinary tract infections in children: EAU/ESPU guidelines.

Authors:  Raimund Stein; Hasan S Dogan; Piet Hoebeke; Radim Kočvara; Rien J M Nijman; Christian Radmayr; Serdar Tekgül
Journal:  Eur Urol       Date:  2014-12-02       Impact factor: 20.096

5.  Comparison of Febrile Infants With Enterococcal and Gram-negative Urinary Tract Infections.

Authors:  Tamar R Lubell; David Schnadower; Stephen B Freedman; Charles G Macias; Dewesh Agrawal; Nathan Kuppermann; Peter S Dayan
Journal:  Pediatr Infect Dis J       Date:  2016-09       Impact factor: 2.129

6.  Early Antibiotic Treatment for Pediatric Febrile Urinary Tract Infection and Renal Scarring.

Authors:  Nader Shaikh; Tej K Mattoo; Ron Keren; Anastasia Ivanova; Gang Cui; Marva Moxey-Mims; Massoud Majd; Harvey A Ziessman; Alejandro Hoberman
Journal:  JAMA Pediatr       Date:  2016-09-01       Impact factor: 16.193

7.  Community-onset urinary tract infections: a population-based assessment.

Authors:  K B Laupland; T Ross; J D D Pitout; D L Church; D B Gregson
Journal:  Infection       Date:  2007-06       Impact factor: 3.553

8.  A simple, step-by-step guide to interpreting decision curve analysis.

Authors:  Andrew J Vickers; Ben van Calster; Ewout W Steyerberg
Journal:  Diagn Progn Res       Date:  2019-10-04

9.  24-hour Serum Creatinine Variation Associates with Short- and Long-Term All-Cause Mortality: A Real-World Insight into Early Detection of Acute Kidney Injury.

Authors:  Hung-Chieh Yeh; Yen-Chun Lo; I-Wen Ting; Pei-Lun Chu; Shih-Ni Chang; Hsiu-Yin Chiang; Chin-Chi Kuo
Journal:  Sci Rep       Date:  2020-04-16       Impact factor: 4.379

10.  Viral etiologies of acute respiratory tract infections among hospitalized children - A comparison between single and multiple viral infections.

Authors:  Chun-Yu Yen; Wan-Tai Wu; Chia-Yuan Chang; Ying-Chi Wong; Chou-Cheng Lai; Yu-Jiun Chan; Keh-Gong Wu; Miao-Chiu Hung
Journal:  J Microbiol Immunol Infect       Date:  2019-09-30       Impact factor: 4.399

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