ArticleJournal of clinical microbiology2016
Evaluation of an Image Analysis Device (APAS) for Screening Urine Cultures.
Article in Journal of clinical microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- Evaluation of an AI-Assisted Colony Counting System Across Multiple Culture Media Using Standardized Pure Culture Plates.Microorganisms · 2026Article
- Comparison of the APAS Independence Automated Plate Reader System with the Manual Standard of Care for Processing Urine Culture Specimens.Microbiology spectrum · 2022Article
- 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.Journal of clinical microbiology · 2021Article
- Laboratory Automation in Clinical Microbiology.Bioengineering (Basel, Switzerland) · 2018Review
- Total Laboratory Automation in Clinical Microbiology: a Micro-Comic Strip.Journal of clinical microbiology · 2018Article
- Multicenter Evaluation of an Image Analysis Device (APAS): Comparison Between Digital Image and Traditional Plate Reading Using Urine Cultures.Annals of laboratory medicine · 2017Article
- Observations on Variations in Manual Reading of Cultures.Journal of clinical microbiology · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While advancements have been made in some areas of pathology with diagnostic materials being screened using image analysis technologies, the reporting of cultures from agar plates remains a manual process. We compared the results for 2,163 urine cultures read by a reference panel of microbiologists, by the routine laboratory process, and by an automated plate reading system, APAS (LBT Innovations Ltd., South Australia). APAS detected colonies with a sensitivity of 99.1% and a specificity of 99.3% on blood agar, while on MacConkey agar, the colony detection sensitivity was 99.4% with a specificity of 99.3%. The device's ability to enumerate growth had an accuracy of 89.2%, and the morphological identification of colonies showed a high level of performance for the colony types typical of Escherichia coli and other enteric bacilli. On blood agar, lactose-fermenting colonies were morphologically identified with a sensitivity of 98.9%, while on MacConkey agar they were identified with a sensitivity of 99.2%. In this first clinical evaluation, APAS demonstrated high performance in the detection, enumeration, and colony classification of isolates compared with that for conventional plate-reading methods. The device found all cases reported by the laboratory and detected the most commonly encountered organisms found in urinary tract infections.
Indexed as
Identifiers
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Registered trials
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.