ArticleJournal of clinical microbiology2014
The automated clinical microbiology laboratory: fact or fantasy?
Article in Journal of clinical microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- Dynamic screening strategies for the control of a prolonged vancomycin-resistant enterococci outbreak: A decade-long study in a Japanese tertiary hospital.Epidemiology and infection · 2026Article
- Evaluation of automated streaking patterns in urine culture for clinical workflow optimization.Scientific reports · 2025Article
- Impact of an analytical intervention to assure the accuracy of LIAISON QuantiFERON-TB Gold Plus results.Journal of clinical microbiology · 2025Article
- Utility of digital images captured after 4 h of incubation on a microbiology laboratory automation system in guiding the work-up of subcultures from positive blood cultures.Journal of clinical microbiology · 2025Article
- Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology.Nature communications · 2023Article
- Inflated Gamma Interferon Response with QuantiFERON-TB Gold Plus Using the Automated Liaison XL Analyzer: a Testing Algorithm To Mitigate False-Positive Results in Low-Incidence Settings.Journal of clinical microbiology · 2023Article
- Evaluation of MetaSystems Automated Fluorescent Microscopy System for the Machine-Assisted Detection of Acid-Fast Bacilli in Clinical Samples.Journal of clinical microbiology · 2022Article
- Consolidation of Clinical Microbiology Laboratories and Introduction of Transformative Technologies.Clinical microbiology reviews · 2020Review
- Evaluation of the Performance of the Cobas CT/NG Test for Use on the Cobas 6800/8800 Systems for Detection ofJournal of clinical microbiology · 2019Article
- Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for the Rapid Detection of Antimicrobial Resistance Mechanisms and Beyond.Clinical microbiology reviews · 2019Review
- 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 · 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
- High-Throughput Testing of Urogenital and Extragenital Specimens for Detection ofEuropean journal of microbiology & immunology · 2017Article
- The Invisible Army.Journal of clinical microbiology · 2017Article
- Evaluation of the Accelerate Pheno System for Fast Identification and Antimicrobial Susceptibility Testing from Positive Blood Cultures in Bloodstream Infections Caused by Gram-Negative Pathogens.Journal of clinical microbiology · 2017Article
- Article
- Automatic Digital Plate Reading for Surveillance Cultures.Journal of clinical microbiology · 2016Article
- New Developments in Clinical Bacteriology Laboratories.Mayo Clinic proceedings · 2016Review
- Evaluation of an Image Analysis Device (APAS) for Screening Urine Cultures.Journal of clinical microbiology · 2016Article
- Standardization of Operator-Dependent Variables Affecting Precision and Accuracy of the Disk Diffusion Method for Antibiotic Susceptibility Testing.Journal of clinical microbiology · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Automated chemistry laboratories dependent on robotic processes are the standard in both academic and large community hospital settings. Diagnostic microbiology manufacturers are betting that robotics will be used for specimen processing, plate reading, and organism identification in the near future. These systems are highly complex and have large footprints and hefty price tags. However, they are touted as being more efficient, rapid, and accurate than standard processes. Certain features, such as image collection, are highly innovative. Hospital administrators may be swayed to institute these new systems because of the promise of the need for fewer skilled workers, higher throughput, and greater efficiency. They also may be swayed by the fact that workers with the requisite clinical microbiology skills are becoming more difficult to find, and this technology should allow fewer skilled workers to handle larger numbers of cultures. In this Point-Counterpoint, Nate Ledeboer, Medical Director, Clinical Microbiology and Molecular Diagnostics, Dynacare Laboratories, and Froedtert Hospital, Milwaukee, WI, will explain why he believes that this approach will become widespread, while Steve Dallas of the University of Texas Health Science Center San Antonio explains why he thinks that this automation may not become widely used.
Indexed as
Identifiers
What OpenQuestion holds
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.