Evidence map›Paper›PMID 40367086›Full record

ArticlePloS one2025

Development of a novel risk score for diagnosing urinary tract infections: Integrating Sysmex UF-5000i urine fluorescence flow cytometry with urinalysis.

Vo Anh Vinh Trang, Thien Tan Tri Tai Truyen, Minh Thuan Nguyen, Huu Phong Mai, Tri Cuong Phan, Son Hoang Phan, Han My Le Nguyen, Huong-Dung Thi Nguyen, Nguyen Hai Dang Le, Man Nhi Tu and 12 more

Abstract read
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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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3 · Its place in the literature

Who cites it

5 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

22 authors.

Vo Anh Vinh TrangBinh Dan Hospital, Ho Chi Minh, Vietnam.
Thien Tan Tri Tai TruyenSchool of Medicine, Tan Tao University, Long An, Vietnam.ORCID https://orcid.org/0000-0001-8129-2532
Minh Thuan NguyenFaculty of Medicine, Nam Can Tho University, Can Tho, Vietnam.
Huu Phong MaiFaculty of Medicine, Nam Can Tho University, Can Tho, Vietnam.
Tri Cuong PhanFaculty of Medicine, Nam Can Tho University, Can Tho, Vietnam.ORCID https://orcid.org/0009-0002-1175-8370
Son Hoang PhanFaculty of Medicine, Nam Can Tho University, Can Tho, Vietnam.
Han My Le NguyenFaculty of Medicine, Nam Can Tho University, Can Tho, Vietnam.
Huong-Dung Thi NguyenFaculty of Medicine, Nam Can Tho University, Can Tho, Vietnam.
Nguyen Hai Dang LeBinh Dan Hospital, Ho Chi Minh, Vietnam.
Man Nhi TuBinh Dan Hospital, Ho Chi Minh, Vietnam.
Vo Thanh Vi HuynhBinh Dan Hospital, Ho Chi Minh, Vietnam.
Hoang Tram Anh NguyenBinh Dan Hospital, Ho Chi Minh, Vietnam.
Dac Bao Han HoBinh Dan Hospital, Ho Chi Minh, Vietnam.
Ngoc Thuy Uyen TranBinh Dan Hospital, Ho Chi Minh, Vietnam.
Nguyen Ha Uyen TranBinh Dan Hospital, Ho Chi Minh, Vietnam.
Bich-Nhat Thi LeBinh Dan Hospital, Ho Chi Minh, Vietnam.
Duc Tuan DoanBinh Dan Hospital, Ho Chi Minh, Vietnam.
Huu Doan PhamBinh Dan Hospital, Ho Chi Minh, Vietnam.
Truong Bao PhanBinh Dan Hospital, Ho Chi Minh, Vietnam.
Phu Phat PhamBinh Dan Hospital, Ho Chi Minh, Vietnam.
Tuan Vinh NguyenBinh Dan Hospital, Ho Chi Minh, Vietnam.
Phuc Cam Hoang NguyenBinh Dan Hospital, Ho Chi Minh, Vietnam.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUrinary tract infections (UTIs) are common globally, and are developing increased antibiotic resistance. Despite being the diagnostic "gold standard," urine culture is limited by slow results and a high rate of false negative findings, leading to treatment delays, higher costs, and overuse of empirical antibiotics. Our study aims to develop a rapid and reliable model to predict clinical outcomes.

methodsFrom January 1st to October 31st, 2023, we enrolled patients with symptoms suggesting UTI from the Outpatient Department of our hospital. Inclusion criteria were patients aged ≥18, initially diagnosed with UTI, available urinalysis, flow cytometry, and urinary culture. Exclusion criteria included failed sample collection and cultures, and pregnant women. A case-control study was conducted, with UTI cases defined as ≥ 10^5 CFU/ µ L and controls as < 10^5 CFU/ µ L, matched for age and sex in a 1:1 ratio. For validation, retrospective cases from July to December 2022 were selected with matching controls. Using urine culture as the gold standard, the predictive model was developed with backward stepwise logistic regression. Model discrimination was assessed using area under the curve (AUC).

resultsIn our discovery cohort, we included 1,335 UTI cases and 1,282 non-UTI controls, with mean ages of 52.9 ± 17.1 years and 51.9 ± 16.4 years, and females of 76.9% and 77.7%. Using 100 cells/uL as a threshold, bacterial counts demonstrated a sensitivity of 91.0% and specificity of 45.7%. Our novel UTIRisk score, developed from urinalysis and flow cytometry parameters, showed strong discrimination for UTI, with a AUC of 0.82 (95% CI: 0.81-0.84). In the validation cohort, the AUC was 0.77 (95% CI: 0.74-0.80). The UTIRisk score exhibited excellent specificity (96.5%) and high positive predictive value (92.6%). The score performed strongly across subgroups, particularly in males and patients aged ≥65.

conclusionsOur UTIRisk score can improve diagnosis, reduce unnecessary urine cultures, optimize antibiotic use, and help control antibiotic resistance in LMICs. Multicenter, and intervention-based studies are warranted before clinical implementation.

Indexed as

Flow CytometryUrinalysisUrinary Tract InfectionsAdultAgedCase-Control StudiesFemaleHumansMaleMiddle AgedRetrospective StudiesRisk Factors

Identifiers

PMID40367086
PMCPMC12077719

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LicenceCC BY
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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.