About: SARS-CoV-2 detection using digital PCR for COVID-19 diagnosis, treatment monitoring and criteria for discharge

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: SARS-CoV-2 detection using digital PCR for COVID-19 diagnosis, treatment monitoring and criteria for discharge Goto Sponge NotDistinct Permalink

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	SARS-CoV-2 detection using digital PCR for COVID-19 diagnosis, treatment monitoring and criteria for discharge
Creator	Li, Min Wang, Jian Cai, Weihua Dong, Jia Lu, Renfei Wang, Yaqi
Source	MedRxiv
abstract	Background: SARS-CoV-2 nucleic acid detection by RT-PCR is one of the criteria approved by China FDA for diagnosis of COVID-19. However, inaccurate test results (for example, high false negative rate and some false positive rate) were reported in both China and US CDC using the RT-PCR method. Inaccurate results are caused by inadequate detection sensitivity of RT-PCR, low viral load in some patients, difficulty to collect samples from COVID-19 patients, insufficient sample loading during RT-PCR tests, and RNA degradation during sample handling process. False negative detection could subject patients to multiple tests before diagnosis can be made, which burdens health care system. Delayed diagnosis could cause infected patients to miss the best treatment time window. False negative detection could also lead to prematurely releasing infected patients who still carry residual SARS-CoV-2 virus. In this case, these patients could infect many others. A high sensitivity RNA detection method to resolve the existing issues of RT-PCR is in need for more accurate COVID-19 diagnosis. Methods: Digital PCR (dPCR) instrument DropX-2000 and assay kits were used to detect SARS-CoV-2 from 108 clinical specimens from 36 patients including pharyngeal swab, stool and blood from different days during hospitalization. Double-blinded experiment data of 108 clinical specimens by dPCR methods were compared with results from officially approved RT-PCR assay. A total of 109 samples including 108 clinical specimens and 1 negative control sample were tested in this study. All of 109 samples, 26 were from 21patients reported as positive by officially approved clinical RT-PCR detection in local CDC and then hospitalized in Nantong Third Hospital. Among the 109 samples, dPCR detected 30 positive samples on ORFA1ab gene, 47 samples with N gene positive, and 30 samples with double positive on ORFA1ab and N genes. Results: The lower limit of detection of the optimize dPCR is at least 10-fold lower than that of RT-PCR. The overall accuracy of dPCR for clinical detection is 96.3%. 4 out 4 of (100 %) negative pharyngeal swab samples checked by RT-PCR were positive judged by dPCR based on the follow-up investigation. 2 of 2 samples in the RT-PCR grey area (Ct value > 37) were confirmed by dPCR with positive results. 1 patient being tested positive by RT-PCR was confirmed to be negative by dPCR. The dPCR results show clear viral loading decrease in 12 patients as treatment proceed, which can be a useful tool for monitoring COVID-19 treatment. Conclusions: Digital PCR shows improved lower limit of detection, sensitivity and accuracy, enabling COVID-19 detection with less false negative and false positive results comparing with RT-PCR, especially for the tests with low viral load specimens. We showed evidences that dPCR is powerful in detecting asymptomatic patients and suspected patients. Digital PCR is capable of checking the negative results caused by insufficient sample loading by quantifying internal reference gene from human RNA in the PCR reactions. Multi-channel fluorescence dPCR system (FAM/HEX/CY5/ROX) is able to detect more target genes in a single multiplex assay, providing quantitative count of viral load in specimens, which is a powerful tool for monitoring COVID-19 treatment.
has issue date	2020-03-30(xsd:dateTime)
bibo:doi	10.1101/2020.03.24.20042689
has license	medrxiv
sha1sum (hex)	218ff40b1e8c25b1b9339d6138d15b404036f4b8
schema:url	https://doi.org/10.1101/2020.03.24.20042689
resource representing a document's title	SARS-CoV-2 detection using digital PCR for COVID-19 diagnosis, treatment monitoring and criteria for discharge
resource representing a document's body	covid:218ff40b1e8c25b1b9339d6138d15b404036f4b8#body_text
is schema:about of	named entity 'digital PCR' named entity 'monitoring' named entity 'digital PCR' named entity 'peer review' named entity '96P' named entity 'RNA' named entity 'dPCR' named entity 'gene' named entity 'peer review' named entity 'medRxiv' named entity 'gene' named entity 'SARS-CoV-2' named entity 'starting stock' named entity 'lung' named entity 'March 30, 2020' named entity 'medRxiv' named entity 'dPCR' named entity 'RT-PCR' named entity 'confidence intervals' named entity 'serial dilution' named entity 'lungs' named entity 'RT-PCR' named entity 'peer review' named entity 'March 30, 2020' named entity 'Fluorescence' named entity 'RT-PCR' named entity 'CDC' named entity 'RT-PCR' named entity 'medRxiv' named entity 'gene' named entity 'peer review' named entity 'medRxiv' named entity 'Cy5' named entity 'false negative' named entity 'RT-PCR' named entity 'microliter' named entity 'RT-PCR' named entity 'medRxiv' named entity 'March 30, 2020' named entity 'asymptomatic' named entity 'March 30, 2020' named entity 'inflammation' named entity 'LOD' named entity 'gene' named entity 'gene' named entity 'dPCR' named entity 'PCR' named entity 'real time PCR' named entity 'asymptomatic' named entity 'serial dilution' named entity 'peer review' named entity 'RNA sequences' named entity 'dPCR' named entity 'serum' named entity 'dPCR' named entity 'phlegm' named entity 'gene' named entity 'medRxiv' named entity 'virus' named entity 'RT-PCR' named entity 'negative control' named entity 'dPCR' named entity 'virus' named entity 'peer review' named entity 'March 30, 2020' named entity 'RT-PCR' named entity 'dPCR' named entity 'peer review' named entity 'RNA extraction' named entity 'CDC' named entity 'RT-PCR' named entity 'virus' named entity 'RT-PCR' named entity 'pneumonia' named entity 'sputum' named entity 'March 30, 2020' named entity 'gene' named entity 'limit of quantification' named entity 'limit of detection' named entity 'RT-PCR'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software