Evidence map›Paper›PMID 29651616›Full record

ArticleEuropean journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology2018

Significant increase in cultivation of Gardnerella vaginalis, Alloscardovia omnicolens, Actinotignum schaalii, and Actinomyces spp. in urine samples with total laboratory automation.

Sabrina Klein, Dennis Nurjadi, Susanne Horner, Klaus Heeg, Stefan Zimmermann, Irene Burckhardt

Abstract read
In one paragraph

Article in European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
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  4. Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Microorganisms · 2021
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Reducing the time between inoculation and first-read of urine cultures using total lab automation significantly reduces turn-around-time of positive culture results with minimal loss of first-read sensitivity.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2019
    Article
  18. Impact of total laboratory automation on workflow and specimen processing time for culture of urine specimens.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2018
    Article
  19. Laboratory Automation in Clinical Microbiology.Bioengineering (Basel, Switzerland) · 2018
    Review
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

6 authors.

Sabrina KleinDepartment of Infectious Diseases, Medical Microbiology, University Hospital Heidelberg, Heidelberg, Germany. Sabrina.klein@med.uni-heidelberg.de.ORCID http://orcid.org/0000-0003-0645-3740
Dennis NurjadiDepartment of Infectious Diseases, Medical Microbiology, University Hospital Heidelberg, Heidelberg, Germany.
Susanne HornerDepartment of Infectious Diseases, Medical Microbiology, University Hospital Heidelberg, Heidelberg, Germany.
Klaus HeegDepartment of Infectious Diseases, Medical Microbiology, University Hospital Heidelberg, Heidelberg, Germany.
Stefan ZimmermannDepartment of Infectious Diseases, Medical Microbiology, University Hospital Heidelberg, Heidelberg, Germany.
Irene BurckhardtDepartment of Infectious Diseases, Medical Microbiology, University Hospital Heidelberg, Heidelberg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While total laboratory automation (TLA) is well established in laboratory medicine, only a few microbiological laboratories are using TLA systems. Especially in terms of speed and accuracy, working with TLA is expected to be superior to conventional microbiology. We compared in total 35,564 microbiological urine cultures with and without incubation and processing with BD Kiestra TLA for a 6-month period each retrospectively. Sixteen thousand three hundred thirty-eight urine samples were analyzed in the pre-TLA period and 19,226 with TLA. Sixty-two percent (n = 10,101/16338) of the cultures processed without TLA and 68% (n = 13,102/19226) of the cultures processed with TLA showed growth. There were significantly more samples with two or more species per sample and with low numbers of colony forming units (CFU) after incubation with TLA. Regarding the type of bacteria, there were comparable amounts of Enterobacteriaceae in the samples, slightly less non-fermenting Gram-negative bacteria, but significantly more Gram-positive cocci, and Gram-positive rods. Especially Alloscardivia omnicolens, Gardnerella vaginalis, Actinomyces spp., and Actinotignum schaalii were significantly more abundant in the samples incubated and processed with TLA. The time to report was significantly lower in the TLA processed samples by 1.5 h. We provide the first report in Europe of a large number of urine samples processed with TLA. TLA showed enhanced growth of non-classical and rarely cultured bacteria from urine samples. Our findings suggest that previously underestimated bacteria may be relevant pathogens for urinary tract infections. Further studies are needed to confirm our findings.

Indexed as

ActinomycetaceaeAutomation, LaboratoryBacteriuriaColony Count, MicrobialEnterobacteriaceaeGardnerella vaginalisHumansRetrospective StudiesUrinary Tract InfectionsActinomyces spp.Actinotignum schaaliiAlloscardovia omnicolensGardnerella vaginalisLaboratory automationUrine

Identifiers

PMID29651616
PMCPMC6015101

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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.