Evidence map›Paper›PMID 35972280›Full record

ArticleMicrobiology spectrum2022

Comparison of the APAS Independence Automated Plate Reader System with the Manual Standard of Care for Processing Urine Culture Specimens.

Megan Chiu, Peiting Kuo, Khrissa Lecrone, Andrew Garcia, Ruohui Chen, Natalie E Quach, Xin M Tu, David T Pride

Abstract read
In one paragraph

Article in Microbiology spectrum, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Megan Chiu *Department of Pathology, UC San Diego Health, San Diego, California, USA.
Peiting Kuo *Department of Pathology, UC San Diego Health, San Diego, California, USA.
Khrissa LecroneDepartment of Pathology, UC San Diego Health, San Diego, California, USA.
Andrew GarciaDepartment of Pathology, UC San Diego Health, San Diego, California, USA.
Ruohui ChenDivision of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, San Diego, California, USA.
Natalie E QuachDivision of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, San Diego, California, USA.ORCID 0000-0001-9382-5826
Xin M TuDivision of Biostatistics and Bioinformatics, Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, San Diego, California, USA.
David T PrideDepartment of Pathology, UC San Diego Health, San Diego, California, USA.ORCID 0000-0001-8161-6015

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urine cultures are among the highest-volume tests in clinical microbiology laboratories and usually require considerable manual labor to perform. We evaluated the APAS Independence automated plate reader system and compared it to our manual standard of care (SOC) for processing urine cultures. The APAS device provides automated image interpretation of urine culture plate growth and sorts those images that require further evaluation. We examined 1,519 specimens over a 4-month period and compared the APAS growth interpretations to our SOC. We found that 72 of the 1,519 total specimens (4.74%) had growth discrepancies, where these specimens were interpreted differently by the APAS and the technologist, which required additional evaluation of plate images on the APAS system. Overall, there were 56 discrepancies in pathogen identification, which were present in 3.69% of the cultures. An additional pathogen was uncovered in a majority of these discrepancies; 12 (21.4%) identified an additional pathogen for the SOC, and 40 (71.4%) identified an additional pathogen for the APAS workflow. We found 214 (2.69%) antimicrobial susceptibility test (AST) discrepancies; 136 (1.71%) minor errors (mEs), 41 (0.52%) major errors (MEs), and 36 (0.45%) very major errors (VMEs). Many of the MEs and VMEs occurred in only a small subset of 13 organisms, suggesting that the specimen may have had different strains of the same pathogens with differing AST results. Given the significant labor required to perform urine cultures, the APAS Independence system has the potential to reduce manual labor while maintaining the identity and AST results of urinary pathogens.

Indexed as

Anti-Infective AgentsStandard of CareMicrobial Sensitivity TestsAnti-Infective Agentsantimicrobial susceptibility testingartificial intelligenceautomationimage processingmachine learningurine cultures

Identifiers

PMID35972280
PMCPMC9603219

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Registered trials

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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.