TY - JOUR
T1 - Efficient automated semi-quantitative urine culture analysis via BD Urine Culture App
AU - Uwamino, Yoshifumi
AU - Nagata, Mika
AU - Aoki, Wataru
AU - Kato, Ai
AU - Daigo, Miho
AU - Ishihara, Osamu
AU - Igari, Hirotaka
AU - Inose, Rika
AU - Hasegawa, Naoki
AU - Murata, Mitsuru
N1 - Funding Information:
This study was funded by Nippon Beckton Dickinson Company, LTD. This work was also supported by Council for Science, Technology and Innovation (CSTI), Cross-ministerial Strategic Innovation Promotion Program (SIP), "Innovative AI Hospital System" (Funding Agency: National Institute of Biomedical Innovation, Health and Nutrition (NIBIOHN)).
Publisher Copyright:
© 2021 Elsevier Inc.
PY - 2022/1
Y1 - 2022/1
N2 - We aimed to assess the clinical utility of BD KiestraTM 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.
AB - We aimed to assess the clinical utility of BD KiestraTM 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.
KW - BD Kiestra™ solution
KW - BD Urine Culture App
KW - Laboratory automation
KW - Semi-quantitative urine culture
UR - http://www.scopus.com/inward/record.url?scp=85118261601&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85118261601&partnerID=8YFLogxK
U2 - 10.1016/j.diagmicrobio.2021.115567
DO - 10.1016/j.diagmicrobio.2021.115567
M3 - Article
C2 - 34731683
AN - SCOPUS:85118261601
SN - 0732-8893
VL - 102
JO - Diagnostic Microbiology and Infectious Disease
JF - Diagnostic Microbiology and Infectious Disease
IS - 1
M1 - 115567
ER -
