Literature DB >> 32920021

Clinical evaluation of the APAS® Independence: Automated imaging and interpretation of urine cultures using artificial intelligence with composite reference standard discrepant resolution.

Lisa Brenton1, Mary Jo Waters2, Tyman Stanford3, Steven Giglio3.   

Abstract

BACKGROUND: This study reports the outcome of the first evaluation of the APAS® Independence for automated reading and preliminary interpretation of urine cultures in the routine clinical microbiology laboratory. In a 2-stage evaluation involving 3000 urine samples, two objectives were assessed; 1) the sensitivity and specificity of the APAS® Independence compared to microbiologists using colony enumeration as the primary determinant, and 2) the variability between microbiologists in enumerating bacterial cultures using traditional culture reading techniques, performed independently to APAS® Independence interpretation.
METHODS: Routine urine samples received into the laboratory were processed and culture plates were interpreted by standard methodology and with the APAS® Independence. Results were compared using typical discrepant result resolution and with a composite reference standard, which provided an alternative assessment of performance.
RESULTS: The significant growth sensitivity of the APAS® Independence was determined to be 0.919 with a 95% confidence interval of (0.879, 0.948), and the growth specificity was 0.877 with a 95% confidence interval of (0.827, 0.916). Variability between microbiologists was demonstrated with microbiologist bi-plate enumerations in agreement with the consensus 88.6% of the time.
CONCLUSION: The APAS® Independence appears to offer microbiology laboratories a mechanism to standardise the processing and assessment of urine cultures whilst augmenting the skills of specialist microbiology staff.
Copyright © 2020 The Author(s). Published by Elsevier B.V. All rights reserved.

Keywords:  APAS; Artificial intelligence; Automation; Discrepant; Imaging

Mesh:

Year:  2020        PMID: 32920021     DOI: 10.1016/j.mimet.2020.106047

Source DB:  PubMed          Journal:  J Microbiol Methods        ISSN: 0167-7012            Impact factor:   2.363


  2 in total

1.  Comparison of an Automated Plate Assessment System (APAS Independence) and Artificial Intelligence (AI) to Manual Plate Reading of Methicillin-Resistant and Methicillin-Susceptible Staphylococcus aureus CHROMagar Surveillance Cultures.

Authors:  Natalie Gammel; Tracy L Ross; Shawna Lewis; Melissa Olson; Susan Henciak; Renee Harris; Ann Hanlon; Karen C Carroll
Journal:  J Clin Microbiol       Date:  2021-08-11       Impact factor: 5.948

2.  Microbiology 2.0-A "behind the scenes" consideration for artificial intelligence applications for interpretive culture plate reading in routine diagnostic laboratories.

Authors:  B DeYoung; M Morales; S Giglio
Journal:  Front Microbiol       Date:  2022-08-04       Impact factor: 6.064

  2 in total

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