Digital PCR is a sensitive new technique for SARS-CoV-2 detection in clinical applications.
Clin Chim Acta
; 511: 346-351, 2020 Dec.
Article
in English
| MEDLINE | ID: covidwho-907115
ABSTRACT
The global coronavirus disease 2019 (COVID-19) pandemic has posed great challenges in people's daily lives. Highly sensitive laboratory techniques played a critical role in clinical COVID-19 diagnosis and management. In this study the feasibility of using a new digital PCR-based detection assay for clinical COVID-19 diagnosis was investigated by comparing its performance with that of RT-PCR. Clinical patient samples and samples obtained from potentially contaminated environments were analyzed. The study included 10 patients with confirmed COVID-19 diagnoses, 32 validated samples of various types derived from different clinical timepoints and sites, and 148 environmentally derived samples. SARS-CoV-2 nucleic acids were more readily detected in respiratory tract samples (35.0%). In analyses of environmentally derived samples, the positivity rate of air samples was higher than that of surface samples, probably due to differences in virus concentrations. Digital PCR detected SARS-CoV-2 in several samples that had previously been deemed negative, including 3 patient-derived samples and 5 environmentally derived samples. In this study digital PCR exhibited higher sensitivity than conventional RT-PCR, suggesting that it may be a useful new method for clinical SARS-CoV-2 detection. Improvement of SARS-CoV-2 detection would substantially reduce the rates of false-negative COVID-19 test results, in particular those pertaining to asymptomatic carriers.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Real-Time Polymerase Chain Reaction
/
Digital Technology
/
SARS-CoV-2
/
COVID-19
Type of study:
Diagnostic study
/
Prognostic study
Limits:
Adult
/
Aged
/
Female
/
Humans
/
Male
/
Middle aged
Language:
English
Journal:
Clin Chim Acta
Year:
2020
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS