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Diagnostic Accuracy of Urine Flow Cytometry in Excluding Bacteruria

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details. Identifier: NCT04686292
Recruitment Status : Recruiting
First Posted : December 28, 2020
Last Update Posted : March 3, 2021
Information provided by (Responsible Party):
University of Southern Denmark

Brief Summary:
A more rapid test for bacteriuria is desired. This will exclude the patients not having bacteriuria, which will contribute to a more rapid and accurate diagnosis of infectious diseases. The aim of the study is to investigate the diagnostic accuracy of point-of-care urine flow cytometry on diagnosing and excluding bacteriuria

Condition or disease Intervention/treatment
Acute Infection Diagnostic Test: urine flow cytometry

Detailed Description:

A prerequisite for the appropriate use of antibiotics is timely access to accurate diagnostic tests, since treatment of acute infections should be initiated within a few hours to avoid serious complications such as bacteremia, sepsis, organ failure, septic shock and death.

The diagnosis of urinary tract infections including acute pyelonephritis (APN) is difficult due to often weak and non-specific symptoms and high incidence of asymptomatic bacteruria in especially elderly patients. The diagnosis is verified by significant bacteriuria in urine culture.

Unfortunately, the time from urine sample to result from urine cultures is more than 24 hours days. Urine test strips are unreliable with low specificity and low predictive values. Therefore, a point-of-care (POC) test is desired, which can provide rapid results and quickly identify a bacteriuria. One such tool may be urine flow cytometry (UFC), which has shown promising diagnostic value for the exclusion of bacteriuria with a high negative predictive value. However, better documentation for its use as an ED diagnostic screening method is needed.

The aim of the study is to investigate the diagnostic accuracy of POC-UFC on diagnosing and excluding bacteriuria? Our hypothesis is that by excluding patients not having bacteriuria, it will contribute to a more rapid and accurate diagnosis

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Study Type : Observational
Estimated Enrollment : 1000 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Diagnostic Accuracy of Urine Flow Cytometry in Diagnosing and Excluding Bacteruria in the Emergency Department
Actual Study Start Date : March 1, 2021
Estimated Primary Completion Date : September 2021
Estimated Study Completion Date : December 2021

Resource links provided by the National Library of Medicine

Group/Cohort Intervention/treatment
Suspected infection
All patients admitted to the emergency department with suspected infections assessed by the receiving physician
Diagnostic Test: urine flow cytometry
Diagnostic test of urine flow cytometry. A urine sample will be collected according to routine procedure by a study assistant. The sample will be divided into two aliquots; half for routine urine culturing, and half for Point-of-care Urine Flow cytometry (POC-UFC) analysis (UF-5000, Sysmex, Kobe, Japan). The analysis will be performed according to manufacturer's instruction and conducted by laboratory staff. Laboratory staff will be blinded to the participants diagnosis and outcome. The results of the POC-UFC analysis will not be visible to the treating physician.

Primary Outcome Measures :
  1. Bacteriuria [ Time Frame: urine collected within 4 hours of arrival to emergency department and analysed within one week ]
    The urine culture analysis combined with microbiologist assessment will be used as reference standard for bacteriuria. Diagnostic accuracy will be conducted, and Youden index analysis will be used to estimate the best cut-off

Secondary Outcome Measures :
  1. Verified infectious diagnosis by expert panel [ Time Frame: 2 months after discharge ]
    An expert panel will define the final diagnosis (including APN) based on all findings during admission. The expert panel consists of two independent consultants from the emergency department with significant experience in emergency medicine and acute infections. They will individually determine the type of infection the patient admitted actually had. The final diagnosis will be based on all available relevant information from the patient medical record including MRI of kidneys and HR-CT of lungs. A standardized template will be used. Disagreement will be discussed until a consensus is reached.

Other Outcome Measures:
  1. Intensive care unit treatment [ Time Frame: within 60 days from admission to emergency department ]
    transfer to ICU during current admission (binary outcome)

  2. Length of stay [ Time Frame: within 60 days from admission to emergency department ]
    days spent in hospital during current admission

  3. The number of participants who died within 30 days [ Time Frame: within 30 days from arrival day ]
    binary - 30-days mortality

  4. The number of participants who died within 90 days [ Time Frame: within 90 days from arrival day ]
    binary - 90 days mortality

  5. Readmission [ Time Frame: within 30 days from day of discharge ]

  6. In-hospital mortality [ Time Frame: within 60 days from admission to emergency department ]

  7. Level of infection markers [ Time Frame: blood collected within 4 hours of arrival to emergency department ]
    Concentration of serum procalcitonin, CRP and suPAR

  8. Urological intervention [ Time Frame: Measured 7 days after admission ]
    Number of patients, who during the course of admission with suspected acute pyelonephritis requires urological interventions

Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Probability Sample
Study Population
Acutely admitted patients with suspected infections from three emergency departments (EDs) in the Region of Southern Denmark (Hospital Sønderjylland, Hospital Lillebælt, Odense University Hospital)

Inclusion Criteria:

  • Suspicion of acute infections assessed by the receiving physician at the emergency department

Exclusion Criteria:

  • If the attending physician considers that participation will delay a life-saving treatment or patient needs direct transfer to the intensive care unit.
  • Admission within the last 14 days
  • Verified COVID-19 disease within 14 days before admission
  • Pregnant women
  • Severe immunodeficiencies: Primary immunodeficiencies and secondary immunodeficiencies (HIV positive CD4 <200, Patients receiving immunosuppressive treatment (ATC L04A), Corticosteroid treatment (>20 mg/day prednisone or equivalent for >14 days within the last 30 days), Chemotherapy within 30 days)

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT04686292

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Contact: Helene Skjøt-Arkil, PhD _45 79971113
Contact: Christian Backer Mogensen +4579971123

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Hospital of Southern Jutland Recruiting
Aabenraa, Denmark
Contact: Christian B Mogensen, MD         
Sponsors and Collaborators
University of Southern Denmark
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Study Chair: Christian Backer Mogensen Hospital of Southern Jutland
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Responsible Party: University of Southern Denmark Identifier: NCT04686292    
Other Study ID Numbers: SHS-ED-12b-2020
First Posted: December 28, 2020    Key Record Dates
Last Update Posted: March 3, 2021
Last Verified: January 2021
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by University of Southern Denmark:
Emergency department
Acute infections
urinary tract infections
Additional relevant MeSH terms:
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