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NCT06976125
Application of a Prediction Model for Directing Antibiotic Use in the Treatment of Urinary Tract Infection in an Ambulatory Setting
NA trial testing Decision Aid-prediction model in Urinary Tract Infections in 47 participants. Currently enrolling.
1 June 2026
Quick facts
| Lead sponsor | University Hospitals Cleveland Medical Center |
|---|---|
| Phase | NA |
| Status | Recruiting now |
| Study type | INTERVENTIONAL |
| Allocation | na |
| Design | single group |
| Masking | none |
| Primary purpose | prevention |
| Enrollment | 47 |
| Start date | 20 February 2026 |
| Primary completion | 1 June 2026 |
| Estimated completion | 1 June 2026 |
| Sites | 1 location across United States |
Drugs / interventions tested
- Decision Aid-prediction model
Conditions studied
- Urinary Tract Infections — all drugs for Urinary Tract Infections →
Sponsor
University Hospitals Cleveland Medical Center
Who can join
18 and older, female only, with Urinary Tract Infections. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
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.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
Verify or expand the search:
- PubMed search for NCT06976125
- Europe PMC full search
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Related trials
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Currently open trials in the same condition.
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- NCT06715306 — Intravenous Versus Oral Treatment of the Main Acute Infections · NA · recruiting
- NCT06702449 — A Study on the Safety and Immune Response of a Urinary Tract Infection (UTI) Vaccine in Adults 18-64 Years of Age and Cl · Phase 1, PHASE2 · recruiting
Other University Hospitals Cleveland Medical Center trials
Trials by the same sponsor.
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT06976125 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by University Hospitals Cleveland Medical Center
- Last refreshed: 8 April 2026
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