Advances and Progress in Automated Urine Analyzers.


Journal

Clinics in laboratory medicine
ISSN: 1557-9832
Titre abrégé: Clin Lab Med
Pays: United States
ID NLM: 8100174

Informations de publication

Date de publication:
Sep 2024
Historique:
medline: 2 8 2024
pubmed: 2 8 2024
entrez: 1 8 2024
Statut: ppublish

Résumé

The clinical analysis of urine has classically focused on conventional chemical-based urinalysis and urine microscopy. Contemporary advances in both analysis subsets have started to employ new technologies such as automated image analysis, flow cytometry, and mass spectrometry. In addition to new detection technologies, current analyzers have incorporated more advanced imaging, automated sample handing, and machine learning analyses into their workflow. The most advanced semiautomated analyzers can be interfaced with hospital medical record systems, and in the point-of-care setting, smartphones can be used for image analysis. This review will discuss current technological advancements in the field of urinalysis and urine microscopy.

Identifiants

pubmed: 39089747
pii: S0272-2712(24)00014-3
doi: 10.1016/j.cll.2024.04.003
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

409-421

Informations de copyright

Copyright © 2024 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Disclosure The authors have nothing to disclose.

Auteurs

Nicholas E Larkey (NE)

Department of Pathology, Division of Clinical Chemistry, University of Virginia Health, 1215 Lee Street, Charlottesville, VA 22903, USA.

Ifeyinwa E Obiorah (IE)

Department of Pathology, Division of Hematopathology, University of Virginia Health, 1215 Lee street, Charlottesville, VA 22903, USA. Electronic address: jnp5qm@uvahealth.org.

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Classifications MeSH