Evidence map›Paper›PMID 40739551›Full record

ArticleBMC infectious diseases2025

Flow cytometry for screening and prioritisation of urine samples: a retrospective comparison with culture.

Vicky Sender, John Kerr White, Ludvig Bolinder, Karin Amilon, Mirja Hägg, Karin Haij Bhattarai, Niklas K Björkström, Baharak Saeedi

Abstract readComparative Study
In one paragraph

Article in BMC infectious diseases, 2025. 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
–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

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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.

  1. Review
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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.

Vicky SenderDepartment of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden. vicky.sender@ki.se.
John Kerr WhiteDepartment of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden.
Ludvig BolinderDepartment of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden.
Karin AmilonDepartment of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden.
Mirja HäggDepartment of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden.
Karin Haij BhattaraiDepartment of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden.
Niklas K BjörkströmDepartment of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden.
Baharak SaeediDepartment of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEfficient urinary tract infection (UTI) diagnostics require reliable methods to rapidly exclude negative samples while accurately identifying positive cases. Automated urine flow cytometry (UFC) offers a promising approach to streamline laboratory workflows by reducing unnecessary cultures and providing early bacterial classification. This study evaluated the performance of a UFC-based screening method compared to conventional urine culture.

methods4005 urine samples were analysed using UFC (Sysmex UF-5000) and compared to culture results. Receiver operating characteristic (ROC) curve analyses assessed method agreement across different patient subpopulations. Predictive values were calculated for the total population and the ten different subpopulations at different cut-offs. Carryover and cross-contamination were also examined.

resultsBased on our data, we propose an algorithm using bacterial count from UFC to guide urine culture decisions. A cut-off of < 30 BACT cells/µl to support exclusion of negative samples (AUC 0.921) could potentially reduce culture rates by ~ 32%. Due to reduced diagnostic performance in subgroup analyses, pregnant women and children were excluded from the rule-out strategy. UFC also demonstrated high sensitivity and specificity in identifying samples likely to be culture-positive, and a cut-off of > 4000 BACT cells/µl was suggested to indicate clinically relevant bacteriuria (AUC 0.917). Pregnant women were excluded from this rule-in approach due to limited discriminatory performance in this subgroup. Additionally, the BACT-Info flag "Gram Neg?" predicted Gram-negative bacteria in 61% of culture-positive samples, with 96% concordance, offering potential early indication of Gram-negative infections.

conclusionsUFC shows potential as a useful screening tool for reducing unnecessary cultures by helping to exclude negative samples and highlighting those likely to be positive. The "Gram Neg?" flag facilitated early differentiation of Gram-negative infections, aiding timely targeted antibiotic therapy. Thus, implementing UFC-based screening in routine diagnostics could reduce laboratory workload while maintaining diagnostic accuracy and patient safety.

Indexed as

Flow CytometryUrinalysisUrinary Tract InfectionsUrineAdolescentAdultAgedAged, 80 and overBacteriaBacteriuriaChildChild, PreschoolFemaleHumansMaleMass ScreeningBacteriuriaFlow cytometryRapid diagnosticsScreeningUrinary tract infectionUrine culture

Identifiers

PMID40739551
PMCPMC12312330

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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.