ADAPT-AST (Adaptive Antimicrobial Susceptibility Testing)

The goal of this study is to improve the way urinary tract infections (UTIs) are tested for antibiotic resistance. The main questions it aims to answer are: * Can the investigators use a method called Bayesian causal inference to create or check clinical prediction models that help predict if certain antibiotics will work for a urinary infection, using patient information from the National Health Service (NHS)? * Can this new ADAPT-AST method, which uses data and a smarter approach, do a better job of testing for urinary infection than the old methods? Will it help doctors make quicker decisions and save resources by being more efficient? Participants in this study will not be receiving treatments. The study will involve: Using statistical methods to predict UTI test results based on patient data. Evaluating whether this new approach can provide doctors with more timely and useful information for treating UTIs. Assessing whether it can help save money and resources in the lab and pharmacy.

NCT Number	NCT06297837
Lead Sponsor	Liverpool University Hospitals NHS Foundation Trust
Conditions	Urinary Tract Infections
Enrollment	500,000 participants
Start Date	2024-09-01
Primary Completion	2025-12 (estimated)
Study Completion	2026-03 (estimated)
Updated on ClinicalTrials.gov	2025-02-04