Abstract

Abstract Objective: The aim of this study was to assess the clinical value of urinary tract infections (UTIs) guideline algorithms and the role of nonspecific symptoms to support clinical decision-making in nursing home residents. Design: In a preplanned secondary analysis of a cross-sectional study including nursing home residents with a presumed UTI, 2 prediction models were used in a decision curve analysis (DCA): (1) guideline-based and (2) extended: nonspecific symptom(s) added to the guideline model. The stringent outcome definition for “true UTIs” included symptom improvement during adequate antimicrobial therapy, based on susceptibility test results. The outcome of a DCA is the Net Benefit to quantify the performance of the prediction models, visualized in a decision curve. Setting: Dutch nursing homes (n = 13). Patients: Nursing home residents with a presumed UTI. Results: Of the 180 residents with a presumed UTI, 43 fulfilled the definition of “true UTI” (23.9%). The Net Benefit of the guideline-based model was low and the corresponding threshold range was small (21%–28%). The extended model improved the prediction of UTIs. However, the clinical usefulness of the extended model was still limited to a small threshold range (10%–28%). Conclusions: The clinical usefulness of the current guideline-based algorithm to diagnose UTI in nursing home residents seems limited, and adding nonspecific symptoms does not further improve decision-making due to the small threshold probability. Given the poor performance of the guideline-based model, refinement of the guidelines may be required. Trial registry: Dutch trial registry: NTR6467; date of first registration, 25/05/2017.