Evidence map›Paper›PMID 38193688›Full record

ArticleMicrobiology spectrum2024

Optimization of the STARlet workflow for semi-automatic SARS-CoV-2 screening of swabs and deep respiratory materials using the RealAccurate Quadruplex SARS-CoV-2 PCR kit and Allplex SARS-CoV-2 PCR kit.

Jacky Flipse, Angelino T Tromp, Danique Thijssen, Nicole van Xanten-Jans-Beken, Roy Pauwelsen, Harmen J van der Veer, Juliëtte M Schlaghecke, Caroline M A Swanink

Open access · goldAbstract read
In one paragraph

Article in Microbiology spectrum, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.6field-weighted citation impact, top 20% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
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 at 3 institutions in 1 country.

Jacky FlipseLaboratory for Medical Microbiology and Immunology, Rijnstate Hospital, Velp, the Netherlands.ORCID 0000-0002-2195-5282
Angelino T TrompLaboratory for Medical Microbiology and Immunology, Rijnstate Hospital, Velp, the Netherlands.
Danique ThijssenLaboratory for Medical Microbiology and Immunology, Rijnstate Hospital, Velp, the Netherlands.
Nicole van Xanten-Jans-BekenLaboratory for Medical Microbiology and Immunology, Rijnstate Hospital, Velp, the Netherlands.
Roy PauwelsenLaboratory for Medical Microbiology and Immunology, Rijnstate Hospital, Velp, the Netherlands.
Harmen J van der VeerLaboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.
Juliëtte M SchlagheckeResearch Group Applied Natural Sciences, Fontys University of Applied Sciences, Eindhoven, the Netherlands.
Caroline M A SwaninkLaboratory for Medical Microbiology and Immunology, Rijnstate Hospital, Velp, the Netherlands.
Rijnstate Hospital · NLEindhoven University of Technology · NLFontys University of Applied Sciences · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic triggered the implementation of large-scale screenings in the health care and in the general population. Consequently, medical laboratories have to apply lean laboratory management to design workflows that are able to process large batches within short turnaround times while maintaining flexibility to use different SARS-CoV-2 reverse transcription polymerase chain reactions (RT-PCRs) and to be able to process a variety of clinical samples. We validated two SARS-CoV-2 PCR assays on the STARlet workflow: Allplex SARS-CoV-2 PCR kit and RealAccurate Quadruplex SARS-CoV-2 PCR kit. Furthermore, we optimized and validated the STARlet workflow for semi-automatic screening for SARS-CoV-2 in upper respiratory swabs and deep respiratory materials (sputa, bronchoalveolar lavage, and aspirate). Strikingly, guanidine-containing lysis buffers allow for easy processing and can enhance sensitivity of SARS-COV-2 screening since sampling in these buffers may preserve viral transcripts as evident by the higher copy numbers of the SARS-CoV-2 N gene. Moreover, using the principles of lean laboratory management, several bottlenecks that are typical for medical laboratories were addressed. We show that lean laboratory management resulted in significant reduction of the turnaround times of the SARS-CoV-2 PCR in our laboratory. This report thus describes a useful framework for laboratories to implement similar semi-automated workflows.IMPORTANCEThe SARS-CoV-2 pandemic triggered the implementation of large-scale screenings in the health care and in the general population. Consequently, medical laboratories had to adapt and evolve workflows that are able to process large batches within short turnaround times while maintaining flexibility to use different assays and to be able to process a variety of clinical samples. We describe how the need for increased outputs and greater flexibility was addressed with respect to clinical samples and assays (Allplex SARS-CoV-2 PCR and RealAccurate Quadruplex SARS-CoV-2 PCR). Strikingly, we found that upper respiratory swabs collected in guanidine-containing lysis buffers both improved the ease of processing as well as enhanced the sensitivity of the SARS-CoV-2 screening. This report thus describes a useful framework for laboratories to implement and optimize similar semi-automated workflows.

Indexed as

COVID-19SARS-CoV-2COVID-19 TestingGuanidinesHumansPolymerase Chain ReactionSensitivity and SpecificityWorkflowGuanidineslaboratorium automationlean managementmolecular diagnosticsSARS-CoV-2turnaround timevalidation

Identifiers

PMID38193688
PMCPMC10846099
OpenAlexW4390760544

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.