Risk prediction model of urinary tract infection in Hospitalized Patients based on evidence-based medicine: systematic review and Meta-analysis
Abstract
BACKGROUND
Urinary tract infection (UTI) is a leading nosocomial infection. Although many UTI risk prediction models have been developed, their methodological quality, predictive performance, and clinical applicability remain unclear. This study aimed to systematically evaluate UTI risk prediction models in hospitalized patients.
METHODS
This systematic review and meta-analysis was registered in PROSPERO (CRD420250643187) and performed in accordance with PRISMA guidelines. Ten databases were searched from inception to March 10, 2025. Study quality was assessed using the PROBAST tool. Meta-analyses were conducted using Stata 14.0 and MedCalc software.
RESULTS
Thirty-four studies involving 323,308 patients and 41 prediction models were included. The median UTI incidence was 18.6%. All studies were rated as high risk of bias, with good applicability. The pooled AUC was 0.849 (95%CI: 0.823-0.875). For predictors with consistent definitions, indwelling catheter use, duration of catheterization, diabetes mellitus, female sex, catheterization frequency, history of UTI, preoperative catheterization, hypoalbuminemia, and renal dysfunction were significantly associated with UTI (all P<0.05).
CONCLUSIONS
Current risk prediction models for UTI in hospitalized patients show moderate discriminative accuracy but are limited by poor methodological quality and insufficient validation. Future studies should adopt rigorous prospective designs, enhance external validation, and optimize modeling…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 323,308 participants or records.
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