Urinary Tract InfectionsADAPT-ASTNCT06297837
ADAPT-AST (Adaptive Antimicrobial Susceptibility Testing)
An observational study of Urinary Tract Infections, run by Liverpool University Hospitals NHS Foundation Trust at 1 site in United Kingdom.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Urinary Tract Infections
- How many people
- 500,000 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 1 Sep 2024to Mar 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients with a suspected Urinary Tract Infection
Who may be able to join
- o The specimens for which AST predictions \& recommendations will be made are urine specimens processed by LCL Microbiology laboratory taken from patients ≥ 18 years old in LUHFT and/or GP locations that grew organisms within the period of the study dataset; these are the only specimens for which AST results will be available to train and test ADAPT-AST. Predictions will be made for all urine specimen types, including mid-stream urines, catheter specimens of urine and nephrostomy urine.
Who cannot join
- Urine specimens processed by LCL that did not grow organisms within the period of the study dataset
- Urine specimens taken from patients < 18 years old
- Predictions will be made for asymptomatic bacteriuria screening specimens in pregnant women who have had specimens sent from a GP, but not those which have been sent from Liverpool Womens' NHS Foundation Trust (LWfT) Predictions for non-bacterial organisms grown in urine (i.e., fungi) will not be made.
Trial locations and contacts
1 site in 1 country.
United Kingdom1 site
Liverpool University Hospitals NHS Foundation Trust
Liverpool, North West
About this study
Official title: Adaptive Prediction of Antimicrobial Susceptibility and Its Implementation to Improve the Management of Urinary Tract Infection
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?
Read more
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.
Read the detailed description
The aim of this study is to develop and evaluate an adaptive informatics approach for laboratory antimicrobial susceptibility testing (AST) for urinary tract infection (UTI) pathogens compared with current practice to improve patient outcomes, reduce AMR risks and reduce waste of laboratory resources.
UTI is a leading cause of community and hospital acquired infection and a major driver of antimicrobial prescribing in primary and secondary care. The continued proliferation of AMR also increasingly limits treatment choices for many UTIs. Despite the importance of UTI, antimicrobial susceptibility testing (AST) of urine specimens is based on inflexible 'one-size-fits' all standard operating procedures (SOPs). Either a very large unfocused panel of antimicrobials is immediately tested (leading to wasted resources), or more commonly, and particularly in low or middle income (LMIC) settings, a selected subset of antimicrobials is tested at day one prior to a second or even third panel of antimicrobials. Such an approach does not adapt to prior information such as previous resistance patterns, antimicrobial prescribing, or demographic information, despite these factors being powerful (strong) predictors of resistance. This results in imprecise, inefficient, and inequitable provision of antimicrobial susceptibility information, which provides suboptimal support of decisions for treatment of UTI.
This project will use statistical techniques based on Bayesian causal inference to predict urine AST results and prioritise testing using patient demographics, prescribing, admission, and microbiology laboratory care data. The clinical utility of resulting algorithms will be evaluated in terms of their ability to increase the number, timeliness and appropriateness of usable AST results available to clinicians, and their ability to reduce laboratory resource costs through better test prioritisation. The anticipated benefits of a successfully developed, evaluated, and implemented system are faster and more precise treatments of UTI in patients with drug-resistant organisms and more efficient resource management, particularly in laboratory and pharmacy workflows.
- Conditions
- Urinary Tract Infections
- Medical subject headings
- Urinary Tract Infections
What is being measured
The primary outcome is the main question the study is designed to answer.
The overall number of susceptible results per panel available at day 1
The overall number of susceptible results per panel available at day 1
Measured: 2 years
Secondary outcomes (7)
The number of susceptible results per panel available for WHO AWaRe Access category agents at day 1
The number of susceptible results per panel available for WHO AWaRe Access category agents at day 1
Measured: 2 years
The number of susceptible results per panel for orally-administrable agents available at day 1
The number of susceptible results per panel for orally-administrable agents available at day 1
Measured: 2 years
The number of susceptible results per panel for intravenously-administrable agents available at day 1
The number of susceptible results per panel for intravenously-administrable agents available at day 1
Measured: 2 years
The proportion of panels with no results available for WHO AWaRe Access category agents at day 1
The proportion of panels with no results available for WHO AWaRe Access category agents at day 1
Measured: 2 years
The proportion of panels with no susceptible results of any kind available at day 1
The proportion of panels with no susceptible results of any kind available at day 1
Measured: 2 years
The proportion of WHO Access agent susceptible results for the agent with the highest utility value
The proportion of WHO Access agent susceptible results for the agent with the highest utility value
Measured: 2 years
The proportion of susceptible results of any kind for the agent with the highest utility value
The proportion of susceptible results of any kind for the agent with the highest utility value
Measured: 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Mar 2024
- Study start1 Sep 2024
- Primary completionDec 2025 (estimated)
- Study completionMar 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Urinary Tract InfectionsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Retrospective
- Enrolment
- 500,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Liverpool University Hospitals NHS Foundation Trust
- Sponsor type
- Other government
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06297837
- Sponsor's protocol ID
- LHS0205
- Acronym
- ADAPT-AST
- Status last verified
- Nov 2024
- First submitted
- 8 Feb 2024
- Last updated
- 4 Feb 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 4 Feb 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Adaptive Prediction of Antimicrobial Susceptibility and Its Implementation to Improve the Management of Urinary Tract Infection
- ClinicalTrials.gov ID
- NCT06297837
- Acronym / sponsor ID
- ADAPT-AST / LHS0205
- Conditions
- Urinary Tract Infections
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 500,000 participants (estimated)
- Lead sponsor
- Liverpool University Hospitals NHS Foundation TrustOther government
- Study start
- 1 Sep 2024 (actual)
- Primary completion
- Dec 2025 (estimated)
- Study completion
- Mar 2026 (estimated)
- First posted
- 7 Mar 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
The aim of this study is to develop and evaluate an adaptive informatics approach for laboratory antimicrobial susceptibility testing (AST) for urinary tract infection (UTI) pathogens compared with current practice to improve patient outcomes, reduce AMR risks and reduce waste of laboratory resources.
UTI is a leading cause of community and hospital acquired infection and a major driver of antimicrobial prescribing in primary and secondary care. The continued proliferation of AMR also increasingly limits treatment choices for many UTIs. Despite the importance of UTI, antimicrobial susceptibility testing (AST) of urine specimens is based on inflexible 'one-size-fits' all standard operating procedures (SOPs). Either a very large unfocused panel of antimicrobials is immediately tested (leading to wasted resources), or more commonly, and particularly in low or middle income (LMIC) settings, a selected subset of antimicrobials is tested at day one prior to a second or even third panel of antimicrobials. Such an approach does not adapt to prior information such as previous resistance patterns, antimicrobial prescribing, or demographic information, despite these factors being powerful (strong) predictors of resistance. This results in imprecise, inefficient, and inequitable provision of antimicrobial susceptibility information, which provides suboptimal support of decisions for treatment of UTI.
This project will use statistical techniques based on Bayesian causal inference to predict urine AST results and prioritise testing using patient demographics, prescribing, admission, and microbiology laboratory care data. The clinical utility of resulting algorithms will be evaluated in terms of their ability to increase the number, timeliness and appropriateness of usable AST results available to clinicians, and their ability to reduce laboratory resource costs through better test prioritisation. The anticipated benefits of a successfully developed, evaluated, and implemented system are faster and more precise treatments of UTI in patients with drug-resistant organisms and more efficient resource management, particularly in laboratory and pharmacy workflows.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with a suspected Urinary Tract Infection
Key inclusion criteria (1 listed)
- o The specimens for which AST predictions \& recommendations will be made are urine specimens processed by LCL Microbiology laboratory taken from patients ≥ 18 years old in LUHFT and/or GP locations that grew organisms within the period of the study dataset; these are the only specimens for which AST results will be available to train and test ADAPT-AST. Predictions will be made for all urine specimen types, including mid-stream urines, catheter specimens of urine and nephrostomy urine.
Key exclusion criteria (3 listed)
- Urine specimens processed by LCL that did not grow organisms within the period of the study dataset
- Urine specimens taken from patients < 18 years old
- Predictions will be made for asymptomatic bacteriuria screening specimens in pregnant women who have had specimens sent from a GP, but not those which have been sent from Liverpool Womens' NHS Foundation Trust (LWfT) Predictions for non-bacterial organisms grown in urine (i.e., fungi) will not be made.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
The overall number of susceptible results per panel available at day 1
Time frame: 2 years
The overall number of susceptible results per panel available at day 1
7 secondary outcomes
The number of susceptible results per panel available for WHO AWaRe Access category agents at day 1
Time frame: 2 years
The number of susceptible results per panel for orally-administrable agents available at day 1
Time frame: 2 years
The number of susceptible results per panel for intravenously-administrable agents available at day 1
Time frame: 2 years
The proportion of panels with no results available for WHO AWaRe Access category agents at day 1
Time frame: 2 years
The proportion of panels with no susceptible results of any kind available at day 1
Time frame: 2 years
The proportion of WHO Access agent susceptible results for the agent with the highest utility value
Time frame: 2 years
The proportion of susceptible results of any kind for the agent with the highest utility value
Time frame: 2 years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 Feb 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Urinary Tract Infections, run by Liverpool University Hospitals NHS Foundation Trust at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 4 Feb 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The overall number of susceptible results per panel available at day 1 (time frame: 2 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 4 Feb 2025.