Shaikh N, et al. - Researchers sought to formulate and investigate a calculator (UTICalc) that could first estimate the probability of urinary tract infection (UTI) based on clinical variables and then update that probability based on laboratory results by appraising the records of febrile children aged 2 to 23 months. Findings illustrated that UTICalc estimated the probability of UTI by assessing the risk factors present in the individual child. Therefore, testing and treatment could be customized, which in turn, would lead to an improvement in the outcomes for children with UTI.

Methods

• Experts reviewed the electronic medical records of febrile children aged 2 to 23 months who were brought to the emergency department of Children’s Hospital of Pittsburgh, Pittsburgh, Pennsylvania.
• They formulated an independent training database comprising 1,686 patients brought to the Emergency Department between January 1, 2007, and April 30, 2013 and a validation database of 384 patients.
• This study included the investigating 5 multivariable logistic regression models for predicting risk of UTI.
• It consisted only of clinical variables; the remaining models incorporated laboratory results.
• Between June 18, 2013, and January 12, 2018, data analysis was conducted.
• Exposures included documented temperature of 38°C or higher in children aged 2 months to less than 2 years.
• Using culture-confirmed UTI as the main outcome, identification of cutoffs for high and low UTI risk for each model served as the main outcome.
• The resultant models were incorporated into a calculation tool, UTICalc, which aided in examining the medical records.

Results

• The study cohort consisted of 2,070 children and the training database comprised 1,686 children, of whom 1,216 (72.1%) were female and 1,167 (69.2%) white.
• The validation database comprised 384 children, of whom 291 (75.8%) were female and 200 (52.1%) white.
• In contrast with the American Academy of Pediatrics algorithm, the clinical model in UTICalc reduced testing by 8.1% (95% CI, 4.2%-12.0%).
• It also decreased the number of UTIs that were missed from 3 cases to none.
• As per the data, compared with empirically treating all children with a leukocyte esterase test result of 1+ or higher, the dipstick model in UTICalc would lead to a reduction in the number of treatment delays by 10.6% (95% CI, 0.9%-20.4%).