Efficient automated semi-quantitative urine culture analysis via BD Urine Culture App

Yoshifumi Uwamino; Mika Nagata; Wataru Aoki; Ai Kato; Miho Daigo; Osamu Ishihara; Hirotaka Igari; Rika Inose; Naoki Hasegawa; Mitsuru Murata

doi:10.1016/j.diagmicrobio.2021.115567

Efficient automated semi-quantitative urine culture analysis via BD Urine Culture App

Diagn Microbiol Infect Dis. 2022 Jan;102(1):115567. doi: 10.1016/j.diagmicrobio.2021.115567. Epub 2021 Oct 2.

Authors

Affiliations

¹ Department of Laboratory Medicine, Keio University School of Medicine, Tokyo, Japan. Electronic address: uwamino@keio.jp.
² Clinical Laboratory, Keio University Hospital, Tokyo, Japan.
³ Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan.
⁴ Department of Laboratory Medicine, Keio University School of Medicine, Tokyo, Japan.

PMID: 34731683
DOI: 10.1016/j.diagmicrobio.2021.115567

Abstract

We aimed to assess the clinical utility of BD Kiestra^TM Urine Culture App (UCA). High concordance rates were observed between the urine culture colony counts obtained by medical technologists and those produced using UCA. This application may increase the efficiency of obtaining semi-quantitative urine culture results.

Keywords: BD Kiestra™ solution; BD Urine Culture App; Laboratory automation; Semi-quantitative urine culture.

MeSH terms

Automation
Bacteriological Techniques / methods*
Urinalysis / methods*
Urine / microbiology*