Building nomogram plots for predicting urinary tract infections in children less than three years of age

Shang Chien Li, Hsin Chi, Fu Yuan Huang, Nan Chang Chiu, Ching Ying Huang, Lung Chang, Yen Hsin Kung, Pei Fang Su, Yu Lin Mau, Jin Yuan Wang, Daniel Tsung Ning Huang

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Background and purpose: Urinary tract infections (UTIs) are the most common bacterial infection in young children. This study aimed to formulate nomogram plots for clinicians to predict UTIs in children aged <3 years by evaluating the risk factors for UTIs in these children. Methods: This retrospective study was conducted at a tertiary medical center from December 2017 to November 2020. Children less than three years of age were eligible for the study if they had undergone both urine culture and urinalysis during the study period. Mixed-effects logistic regression models with a stepwise procedure were used to determine the relationship between outcome (positive/negative UTI) and covariates of interest (e.g., weight percentile, laboratory) for each patient. Nomogram plots were constructed on the basis of significant factors. We repeated the analysis thrice to adapt it to three different medical settings: medical centers, regional hospitals, and local clinics. Results: In the medical center setting, the two most significant factors were urine leukocyte count ≥100 (OR =8.87; 95% CI (Confidence Interval), 4.135–19.027) and urine nitrite level (OR =8.809; 95% CI, 5.009–15.489). The two factors showed similar significance at the regional hospital and local clinic settings. Abnormal renal echo findings were positively correlated with UTI in the medical center setting (OR =2.534; 95% CI 1.757–3.655). Three nomogram plots for the prediction of UTIs were drawn for medical centers, regional hospitals, and local clinics. Conclusion: Using the three nomogram plots, frontline doctors can formulate the probabilities of pediatric UTIs for better decision-making.

Original languageEnglish
Pages (from-to)111-119
Number of pages9
JournalJournal of Microbiology, Immunology and Infection
Volume56
Issue number1
DOIs
Publication statusPublished - 2023 Feb

All Science Journal Classification (ASJC) codes

  • Immunology and Allergy
  • General Immunology and Microbiology
  • Microbiology (medical)
  • Infectious Diseases

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