Evidence map›Paper›PMID 30944667›Full record

Observational studyDisease markers2019

Diagnosis of Urinary Tract Infections by Urine Flow Cytometry: Adjusted Cut-Off Values in Different Clinical Presentations.

Sabine K Schuh, Ruth Seidenberg, Spyridon Arampatzis, Alexander B Leichtle, Wolf E Hautz, Aristomenis K Exadaktylos, Clyde B Schechter, Martin Müller

Abstract readObservational Study
In one paragraph

Observational study in Disease markers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Sabine K SchuhDepartment of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Ruth SeidenbergDepartment of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Spyridon ArampatzisDepartment of Nephrology, Hypertension and Clinical Pharmacology, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland.
Alexander B LeichtleDepartment of Clinical Chemistry and Insel Data Science Center (IDSC), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0002-6528-9904
Wolf E HautzDepartment of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Aristomenis K ExadaktylosDepartment of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Clyde B SchechterDepartment of Family & Social Medicine & Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA.
Martin MüllerDepartment of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0003-4067-7174

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBacterium and leucocyte counts in urine can be measured by urine flow cytometry (UFC). They are used to predict significant bacterial growth in urine culture and to diagnose infections of the urinary tract. However, little information is available on appropriate UFC cut-off values for bacterium and leucocyte counts in specific clinical presentations.

objectiveTo develop, validate, and evaluate adapted cut-off values that result in a high negative predictive value for significant bacterial growth in urine culture in common clinical presentation subgroups.

methodsThis is a single center, retrospective, observational study with data from patients of the emergency department of Bern University Hospital, Switzerland, with suspected infections of the urinary tract. The patients presented with different symptoms, and urine culture and urine flow cytometry were performed. For different clinical presentations, the patients were grouped by (i) age (>65 years), (ii) sex, (iii) clinical symptoms (e.g., fever or dysuria), and (iv) comorbidities such as diabetes and immunosuppression. For each group, cut-off values were developed, validated, and analyzed using different strategies, i.e., linear discriminant analysis (LDA) and Youden's index, and were compared with known cut-offs and cut-offs optimized for sensitivity.

results613 patients were included in the study. Significant bacterial growth in urine culture depended on clinical presentation and ranged from 32.3% in male patients to 61.5% in patients with urinary frequency. In all clinical presentations, the predictive accuracy of UFC leucocyte and UFC bacterium counts was good for significant bacterial growth in urine culture (AUC ≥ 0.88). The adapted LDA

conclusionsFor various clinical presentations, significant bacterial growth in urine culture can be excluded if flow cytometry measurements give a bacterial count of ≤125/

Indexed as

AgedBacterial LoadFemaleFlow CytometryHumansLeukocyte CountMaleMiddle AgedUrinary Tract InfectionsUrine

Identifiers

PMID30944667
PMCPMC6421762

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