Evidence map›Paper›PMID 33426721›Full record

ArticleJournal of clinical laboratory analysis2021

Evaluation of the detection ability of uropathogen morphology and vaginal contamination by the Atellica UAS800 automated urine microscopy analyzer and its effectiveness.

Akihiro Nakamura, Tetsuya Shinke, Nobuyoshi Noguchi, Masaru Komatsu, Hachiro Yamanishi

Open access · goldAbstract read
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Article in Journal of clinical laboratory analysis, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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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

5 authors at 2 institutions in 1 country.

Akihiro NakamuraDepartment of Clinical Laboratory Science, Faculty of Health Care, Tenri Health Care University, Tenri, Japan.ORCID https://orcid.org/0000-0003-2065-6720
Tetsuya ShinkeDepartment of Clinical Bacteriology, Clinical Laboratory Medicine, Tenri Hospital, Tenri, Japan.
Nobuyoshi NoguchiDepartment of Clinical Laboratory Science, Faculty of Health Care, Tenri Health Care University, Tenri, Japan.
Masaru KomatsuDepartment of Clinical Laboratory Science, Faculty of Health Care, Tenri Health Care University, Tenri, Japan.
Hachiro YamanishiDepartment of Clinical Laboratory Science, Faculty of Health Care, Tenri Health Care University, Tenri, Japan.
Tenri Health Care University · JPTenri Hospital · JP

Funding

Tenri Health Care University
6 · The paper itself

Abstract

backgroundTo help combat the worldwide spread of multidrug-resistant Enterobacterales, which are responsible for many causes of urinary tract infection (UTI), we evaluated the ability of the Atellica UAS800 automated microscopy system, the only one offering the capability of bacterial morphological differentiation, to determine its effectiveness.

methodsWe examined 118 outpatient spot urine samples in which pyuria and bacteriuria were observed using flow cytometry (training set: 81; cross-validation set: 37). The ability of the Atellica UAS800 to differentiate between bacilli and cocci was verified. To improve its ability, multiple logistic regression analysis was used to construct a prediction formula.

resultsThis instrument's detection sensitivity was 106 CFU/ml, and reproducibility in that range was good, but data reliability for the number of cocci was low. Multiple logistic regression analysis with each explanatory variable (14 items from the Atellica UAS800, age and sex) showed the best prediction formula for discrimination of uropathogen morphology was a model with 5 explanatory variables: number of bacilli (p < 0.001), squamous epithelial cells (p = 0.004), age (p = 0.039), number of cocci (p = 0.107), and erythrocytes (p = 0.111). For a predicted cutoff value of 0.449, sensitivity was 0.879 and specificity was 0.854. In the cross-validation set, sensitivity was 0.813 and specificity was 0.857.

conclusionsThe Atellica UAS800 could detect squamous epithelial cells, an indicator of vaginal contamination, with high sensitivity, which further improved performance. Simultaneous use of this probability prediction formula with urinalysis results may facilitate real-time prediction of uropathogens and vaginal contamination, thus providing helpful information for empiric therapy.

Indexed as

AgedAged, 80 and overAutomation, LaboratoryBacteriuriaFemaleHumansLimit of DetectionLogistic ModelsMaleMicroscopyMiddle AgedPyuriaReproducibility of ResultsSensitivity and SpecificityUrinary Tract InfectionsUrineautomated urine microscopy analysismultivariable logistic regression analysisurinary tract infectionuropathogens morphologyvaginal contamination

Identifiers

PMID33426721
PMCPMC7957992
OpenAlexW3119163986

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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.