Evidence map›Paper›PMID 33091046›Full record

ArticlePloS one2020

A diagnostic algorithm for detection of urinary tract infections in hospitalized patients with bacteriuria: The "Triple F" approach supported by Procalcitonin and paired blood and urine cultures.

Kathrin Rothe, Christoph D Spinner, Birgit Waschulzik, Christian Janke, Jochen Schneider, Heike Schneider, Krischan Braitsch, Christopher Smith, Roland M Schmid, Dirk H Busch and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 46% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

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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

11 authors at 4 institutions in 3 countries.

Kathrin RotheInstitute for Medical Microbiology, Immunology and Hygiene, School of Medicine, Technical University of Munich, Munich, Germany.ORCID 0000-0002-8293-5832
Christoph D SpinnerDepartment of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.ORCID 0000-0002-3875-5367
Birgit WaschulzikInstitute of Medical Informatics, Statistics and Epidemiology, School of Medicine, Technical University of Munich, Munich, Germany.ORCID 0000-0001-6365-7972
Christian JankeDivision of Infectious Diseases and Tropical Medicine, University Hospital, LMU Munich, Munich, Germany.
Jochen SchneiderDepartment of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.
Heike SchneiderDepartment of Clinical Chemistry and Pathobiochemistry, School of Medicine, Technical University of Munich, Munich, Germany.
Krischan BraitschDepartment of Internal Medicine III, School of Medicine, Technical University of Munich, Munich, Germany.
Christopher SmithSchool of Tropical Medicine and Global Health (TMGH), Nagasaki University, Nagasaki, Japan.
Roland M SchmidDepartment of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.
Dirk H BuschInstitute for Medical Microbiology, Immunology and Hygiene, School of Medicine, Technical University of Munich, Munich, Germany.
Juri KatchanovDepartment of Internal Medicine II, School of Medicine, Technical University of Munich, Munich, Germany.
Technical University of Munich · DEGerman Center for Infection Research · DELMU Klinikum · DELondon School of Hygiene & Tropical Medicine · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For acute medicine physicians, distinguishing between asymptomatic bacteriuria (ABU) and clinically relevant urinary tract infections (UTI) is challenging, resulting in overtreatment of ABU and under-recognition of urinary-source bacteraemia without genitourinary symptoms (USB). We conducted a retrospective analysis of ED encounters in a university hospital between October 2013 and September 2018 who met the following inclusion criteria: Suspected UTI with simultaneous collection of paired urinary cultures and blood cultures (PUB) and determination of Procalcitonin (PCT). We sought to develop a simple algorithm based on clinical signs and PCT for the management of suspected UTI. Individual patient presentations were retrospectively evaluated by a clinical "triple F" algorithm (F1 ="fever", F2 ="failure", F3 ="focus") supported by PCT and PUB. We identified 183 ED patients meeting the inclusion criteria. We introduced the term UTI with systemic involvement (SUTI) with three degrees of diagnostic certainty: bacteremic UTI (24.0%; 44/183), probable SUTI (14.2%; 26/183) and possible SUTI (27.9%; 51/183). In bacteremic UTI, half of patients (54.5%; 24/44) presented without genitourinary symptoms. Discordant bacteraemia was diagnosed in 16 patients (24.6% of all bacteremic patients). An alternative focus was identified in 67 patients, five patients presented with S. aureus bacteremia. 62 patients were diagnosed with possible UTI (n = 20) or ABU (n = 42). Using the proposed "triple F" algorithm, dichotomised PCT of < 0.25 pg/ml had a negative predictive value of 88.7% and 96.2% for bacteraemia und accordant bacteraemia respectively. The application of the algorithm to our cohort could have resulted in 33.3% reduction of BCs. Using the diagnostic categories "possible" or "probable" SUTI as a trigger for initiation of antimicrobial treatment would have reduced or streamlined antimicrobial use in 30.6% and 58.5% of cases, respectively. In conclusion, the "3F" algorithm supported by PCT and PUB is a promising diagnostic and antimicrobial stewardship tool.

Indexed as

AgedAged, 80 and overAlgorithmsBacteremiaBacteriuriaBloodBlood CultureCohort StudiesFemaleHumansMaleMiddle AgedProcalcitoninStaphylococcus aureusUrinary Tract InfectionsUrineProcalcitonin

Identifiers

PMID33091046
PMCPMC7580978
OpenAlexW3094247010

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.