UTICalc: Tool to Predict Urinary Tract Infection Risk

Researchers from University of Pittsburgh have developed a prediction tool that allows clinicians to identify children (2-23 months) most likely to have a urinary track infection (UTI).

Description

The tool, UTICalc, determines the risk of pediatric UTI based on clinical variables including age, sex, duration, and source of fever, and history of previous UTIs. Clinicians are presented with a probability of UTI to assist with their clinical decision making. This tool allows clinicians to tailor testing and treatment regimens, improving outcomes in children with UTIs.

Applications

Pediatric UTI risk prediction

Advantages

Close to 7% of children under 2 years of age presenting to an emergency department with a fever have a UTI. Diagnosis can be challenging due to difficulty in obtaining a suitable urine sample, with invasive catheterization required. Given the complex nature of this procedure in very young children, clinicians will often only catheterize if the risk of a UTI is deemed sufficiently high. However, accurately determining the risk remains elusive, and as no widely used prediction tool exists, leads to unnecessary catheterization of patients at lower risk and missed diagnosis in others

UTICalc is designed to be an easy-to-use tool to assist clinicians in identifying children likely to require urine analysis based on clinical variables. Following urine analysis, UTICalc can also be used to update the probability of UTI based on the results of laboratory testing.

Invention Readiness

Based on retrospective review of medical records from over 1600 febrile children assessed for UTIs over 6 years, a training database was used to develop a tool to predict risk of UTIs in those aged 2-23 months. This work led to the development of UTICalc through the identification of key clinical risk factors; age <12 months, temperature ?39 °C, nonblack race, female or uncircumcised male, and no other fever source. The developed UTICalc was validated against another database of febrile children and shown to accurately predict UTI risk, reducing the need for invasive testing by 8.1%, substantially decreasing treatment delays, and decreasing the number of UTI diagnoses missed. A website: https://uticalc.pitt.edu/ has been developed to make this tool availalbe to clinicians.

IP Status

Copyright