Urinary Tract InfectionsNCT06976125
Application of a Prediction Model for Directing Antibiotic Use in the Treatment of Urinary Tract Infection in an Ambulatory Setting
A study testing Decision Aid-prediction model in people with Urinary Tract Infections, run by University Hospitals Cleveland Medical Center at 1 site in United States.
Trial summary
Urinary tract infection (UTI) is when bacteria enter the urinary system and cause an infection. UTIs cause symptoms including burning when peeing, a feeling of an increased urge to pee, and cloudy or strong-smelling urine. Sometimes, severe UTIs can also cause fever, abdominal pain, and/or lower back pain. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Urinary Tract Infections
- What is being tested?
- Decision Aid-prediction model
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 47 participants
- Where
- 1 siteUnited States
- Study dates
- 20 Feb 2026to 15 Dec 2026
- Phase
- Interventional
- 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
- Women only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Female sex
- Age >18 years old
- Discharged from the hospital after ER visit
- Discharge ICD code consistent with a UTI diagnosis
- Antibiotic prescribed for UTI at the time of discharge
Who cannot join
- Male sex
- Necessity for chronic bladder catheterization or discharge with a urinary catheter
- Patients who have an Emergency Severity Index (ESI) of 1 and 2
- Patients who verbalize to the study team member that their pain is a 6 or higher
- Patient set to be transferred to inpatient care
- History of bladder augmentation
- Pregnancy (this will be confirmed with a negative pregnancy test which is ordered in the ER)
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
University Hospitals Cleveland Medical Center
Cleveland, Ohio, 44106
Mofetoluwa Abraham Oluwasanmi, 440-317-2777, mofetoluwa.oluwasanmi@uhhospitals.org
About this study
Urinary tract infection (UTI) is when bacteria enter the urinary system and cause an infection. UTIs cause symptoms including burning when peeing, a feeling of an increased urge to pee, and cloudy or strong-smelling urine. Sometimes, severe UTIs can also cause fever, abdominal pain, and/or lower back pain.
In the emergency department (ED), healthcare providers rely on symptoms, along with a urine analysis and a urine culture to diagnose a UTI. A urine analysis involves taking a sample of urine and analyzing different factors like color, acidity, presence of blood cells, presence of bacteria. An abnormal urine analysis increases the likelihood that patients might have a UTI, but it does not confirm it. A positive urine analysis will lead to provider's sending a sample of urine for a urine culture. A urine culture is used to grow whatever bacteria is in the collected urine. If growth is seen on the culture, then this confirms a patient has a UTI. This also specifies which bacteria grew on the culture. The lab can also take it a step further and do an antibiotic test to check which antibiotic the bacteria is sensitive to.
Read more
When a urine analysis comes back abnormal in an ER setting, patients are prescribed an antibiotic before the culture and antibiotic sensitivity tests come back. If a patients condition is not critical, they will be discharged home before the culture results come back. If the culture comes back positive, the pharmacists will evaluate the culture and antibiotic sensitivity tests, then call patients to inform them whether they are taking a suitable antibiotic.
This study aims to decrease the unnecessary use of antibiotics because this contributes to antibiotic resistance which is considered a global public health issue. Antibiotic resistance occurs when bacteria develop the ability to withstand certain antibiotics that used to be effective against them, which makes it difficult to treat the infection. One of the factors that increase the risk of antibiotic resistance is the overuse of antibiotics.
In this study, investigators will be incorporating a prediction model and a negative callback system to decrease unnecessary antibiotic use.
- Conditions
- Urinary Tract Infections
- Being tested
- Decision Aid-prediction model
- Keywords
- ER visits, Antibiotic use
- Medical subject headings
- Urinary Tract Infections
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Decision Aid-prediction modelDevice
ER physician will input the necessary de-identified data into the decision aid application.
The decision aid determines if the patient has a high or low likelihood of having a positive urine culture. The patient with high likelihood of positive culture, will be prescribed empiric antibiotics per the UH guidelines for treating UTI in the ambulatory setting. Patients with a low likelihood of having a positive culture, will be discharged without antibiotics.
Study team members will give the patient a handout describing what will happen in the event of a positive or negative culture.
The culture call-back team, consisting of clinical pharmacists, will be notified.
| Study group | Role | What they receive |
|---|---|---|
| Presenting to ER for Urinary Tract Infection (UTI) | Experimental | Patients presenting to the a UH ER location for UTI symptoms. Receives: Device: Decision Aid-prediction model |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of antibiotic free days as measured by medical record review.
Measured: Up to 2 weeks
Secondary outcomes (7)
Percentage of antibiotic prescriptions for patients discharged from the ER as measured by medical record review.
Measured: Up to 2 weeks
Number of hospitalization since index ER visits as measured by medical record review.
Measured: Up to 2 weeks
Number of ER readmission as measured by medical record review.
Measured: Up to 2 weeks
Number of unscheduled primary care visits as measured by medical record review.
Measured: Up to 2 weeks
Percent of false positive urinalysis as measured by discordance with culture obtained at time of ER visist
Measured: Baseline
Percent of false negative urinalysis as measured by discordance with culture obtained at time of ER visist
Measured: Baseline
Percentage of non-UTI associated urologic diagnoses as measured by medical record review
Measured: Up to 2 weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 May 2025
- Study start20 Feb 2026
- Primary completion1 Dec 2026 (estimated)
- Study completion15 Dec 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.
- More trials run by University Hospitals Cleveland Medical CenterThe sponsor's other registered studies.
- 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 47 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University Hospitals Cleveland Medical Center
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, David Sheyn, Case Western Reserve University
- Investigators
- David Sheyn, MD, Principal investigator, University Hospitals Cleveland Medical Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06976125
- Sponsor's protocol ID
- STUDY20250812
- Status last verified
- Jul 2026
- First submitted
- 9 May 2025
- Last updated
- 6 Jul 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 6 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Application of a Prediction Model for Directing Antibiotic Use in the Treatment of Urinary Tract Infection in an Ambulatory Setting
- ClinicalTrials.gov ID
- NCT06976125
- Acronym / sponsor ID
- STUDY20250812
- Conditions
- Urinary Tract Infections
- Keywords
- ER visits, Antibiotic use
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 47 participants (estimated)
- Lead sponsor
- University Hospitals Cleveland Medical CenterUniversity, hospital or other
- Study start
- 20 Feb 2026 (actual)
- Primary completion
- 1 Dec 2026 (estimated)
- Study completion
- 15 Dec 2026 (estimated)
- First posted
- 16 May 2025 (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.
Urinary tract infection (UTI) is when bacteria enter the urinary system and cause an infection. UTIs cause symptoms including burning when peeing, a feeling of an increased urge to pee, and cloudy or strong-smelling urine. Sometimes, severe UTIs can also cause fever, abdominal pain, and/or lower back pain.
In the emergency department (ED), healthcare providers rely on symptoms, along with a urine analysis and a urine culture to diagnose a UTI. A urine analysis involves taking a sample of urine and analyzing different factors like color, acidity, presence of blood cells, presence of bacteria. An abnormal urine analysis increases the likelihood that patients might have a UTI, but it does not confirm it. A positive urine analysis will lead to provider's sending a sample of urine for a urine culture. A urine culture is used to grow whatever bacteria is in the collected urine. If growth is seen on the culture, then this confirms a patient has a UTI. This also specifies which bacteria grew on the culture. The lab can also take it a step further and do an antibiotic test to check which antibiotic the bacteria is sensitive to.
When a urine analysis comes back abnormal in an ER setting, patients are prescribed an antibiotic before the culture and antibiotic sensitivity tests come back. If a patients condition is not critical, they will be discharged home before the culture results come back. If the culture comes back positive, the pharmacists will evaluate the culture and antibiotic sensitivity tests, then call patients to inform them whether they are taking a suitable antibiotic.
This study aims to decrease the unnecessary use of antibiotics because this contributes to antibiotic resistance which is considered a global public health issue. Antibiotic resistance occurs when bacteria develop the ability to withstand certain antibiotics that used to be effective against them, which makes it difficult to treat the infection. One of the factors that increase the risk of antibiotic resistance is the overuse of antibiotics.
In this study, investigators will be incorporating a prediction model and a negative callback system to decrease unnecessary antibiotic use.
Study design
- Primary purpose
- Prevention
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Presenting to ER for Urinary Tract Infection (UTI) | Experimental | Device: Decision Aid-prediction modelPatients presenting to the a UH ER location for UTI symptoms. |
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- Female sex
- Age >18 years old
- Discharged from the hospital after ER visit
- Discharge ICD code consistent with a UTI diagnosis
- Antibiotic prescribed for UTI at the time of discharge
Key exclusion criteria (7 listed)
- Male sex
- Necessity for chronic bladder catheterization or discharge with a urinary catheter
- Patients who have an Emergency Severity Index (ESI) of 1 and 2
- Patients who verbalize to the study team member that their pain is a 6 or higher
- Patient set to be transferred to inpatient care
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Decision Aid-prediction modelER physician will input the necessary de-identified data into the decision aid application. The decision aid determines if the patient has a high or low likelihood of having a positive urine culture. The patient with high likelihood of positive culture, will be prescribed empiric antibiotics per the UH guidelines for treating UTI in the ambulatory setting. Patients with a low likelihood of having a positive culture, will be discharged without antibiotics. Study team members will give the patient a handout describing what will happen in the event of a positive or negative culture. The culture call-back team, consisting of clinical pharmacists, will be notified. | Device | Presenting to ER for Urinary Tract Infection (UTI) |
Primary outcome
Number of antibiotic free days as measured by medical record review.
Time frame: Up to 2 weeks
7 secondary outcomes
Percentage of antibiotic prescriptions for patients discharged from the ER as measured by medical record review.
Time frame: Up to 2 weeks
Number of hospitalization since index ER visits as measured by medical record review.
Time frame: Up to 2 weeks
Number of ER readmission as measured by medical record review.
Time frame: Up to 2 weeks
Number of unscheduled primary care visits as measured by medical record review.
Time frame: Up to 2 weeks
Percent of false positive urinalysis as measured by discordance with culture obtained at time of ER visist
Time frame: Baseline
Percent of false negative urinalysis as measured by discordance with culture obtained at time of ER visist
Time frame: Baseline
Percentage of non-UTI associated urologic diagnoses as measured by medical record review
Time frame: Up to 2 weeks
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 6 Jul 2026.
- Individual participant dataSharing planned: No
Related trials for Urinary Tract Infections
Recruiting
Diagnosis and Treatment of Urinary Tract Infection Using DNA Polymerase Chain Reaction Versus Urine Culture
Urinary Tract Infections
Active, not recruitingObservational study
Clinical Performance Evaluation of the QIAstat-Dx® cUTI Plus AMR
Complicated Urinary Tract Infection
Active, not recruitingPhase 1/2
A Beta-only IL-2 ImmunoTherapY Study
Advanced Solid Tumor, Unresectable Solid Tumor
Recruiting
INterest of the Negative Predictive Value of Integrons in the reduCtion of Large Broad-spectrum anTibiotics Consumption for Urinary Tract infectionS
Drug Resistance, Microbial, Biomarkers
Not yet recruitingObservational study
Comparative Study of the Genomic Characteristics of Uropathogenic Escherichia Coli According to the Severity of Community-Acquired Urinary Tract Infections in Guadeloupe (COLIGENURI)
Urinary Tract Infections
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.
David Sheyn, MD principal investigator
University Hospitals Cleveland Medical Center
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Decision Aid-prediction model in people with Urinary Tract Infections, run by University Hospitals Cleveland Medical Center at 1 site in United States.
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 5 inclusion and 7 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: looking for participants now, as of the sponsor's last update on 6 Jul 2026. 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 States. 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?
Contact Jessica Abou Zeki (216-286-0603, Jessica.AbouZeki@UHhospitals.org), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of antibiotic free days as measured by medical record review. (time frame: Up to 2 weeks). 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 6 Jul 2026.