About: Computer-aided medical microbiology monitoring tool: a strategy to adapt to the SARS-CoV-2 epidemic and that highlights RT-PCR consistency

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About: Computer-aided medical microbiology monitoring tool: a strategy to adapt to the SARS-CoV-2 epidemic and that highlights RT-PCR consistency Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Computer-aided medical microbiology monitoring tool: a strategy to adapt to the SARS-CoV-2 epidemic and that highlights RT-PCR consistency
Creator	Greub, Gilbert Scherz, Valentin Jaton, Katia Opota, Onya Mueller, Linda
source	MedRxiv
abstract	Since the beginning of the COVID-19 pandemic, important health and regulatory decisions relied on the SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) results. Our diagnostic laboratory faced a rapid increase in the number of SARS-CoV-2 RT-PCR, with up to 1,007 tests per day. To maintain a rapid turnaround time to support patient management and public health authorities' decisions, we moved from a case-by-case validation of RT-PCR to an automated validation and immediate transmission of the results to clinicians. To maintain high quality and to track possible aberrant results, we developed a quality-monitoring tool based on a homemade algorithm coded in R. We present the results of this quality-monitoring tool applied to 35,137 RT-PCR results corresponding to 30,198 patients. Patients tested several times led to 4,939 pairwise comparisons; 88% concordant and 12% discrepant. Among the 573 discrepancies, 428 were automatically solved by the algorithm. The most likely explanation for these 573 discrepancies was related for 44.9% of the situations to %22Clinical evolution%22, 27.9% to %22Preanalytical%22 problems, and 25.3% to %22Stochastic%22. Finally, 11 discrepant results could not be explained, including 8 received from external partners for which clinical data were not available. The implemented quality-monitoring strategy allowed to: i) assist the investigation of discrepant results ii) focus the attention of medical microbiologists onto results requiring a specific expertise and iii) maintain an acceptable TAT. This work highlighted the high RT-PCR consistency for the detection of SARS-CoV-2 and the importance of automated processes to handle a huge number of samples while preserving quality.
has issue date	2020-07-29(xsd:dateTime)
bibo:doi	10.1101/2020.07.27.20162123
has license	medrxiv
sha1sum (hex)	31baefd2a992342a9db115ca64ff6f165db9e8bd
schema:url	https://doi.org/10.1101/2020.07.27.20162123
resource representing a document's title	Computer-aided medical microbiology monitoring tool: a strategy to adapt to the SARS-CoV-2 epidemic and that highlights RT-PCR consistency
resource representing a document's body	covid:31baefd2a992342a9db115ca64ff6f165db9e8bd#body_text
is schema:about of	named entity 'COVID-19 pandemic' named entity 'algorithm' named entity 'medical microbiologists' named entity 'algorithm' named entity 'SARS-CoV-2' »more»

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