ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimens.
Emerg Microbes Infect
; 9(1): 1259-1268, 2020 Dec.
Article
in English
| MEDLINE | ID: covidwho-342833
ABSTRACT
Quantitative real time PCR (RT-PCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. However, due to the low viral load specimens and the limitations of RT-PCR, significant numbers of false negative reports are inevitable, which results in failure to timely diagnose, cut off transmission, and assess discharge criteria. To improve this situation, an optimized droplet digital PCR (ddPCR) was used for detection of SARS-CoV-2, which showed that the limit of detection of ddPCR is significantly lower than that of RT-PCR. We further explored the feasibility of ddPCR to detect SARS-CoV-2 RNA from 77 patients, and compared with RT-PCR in terms of the diagnostic accuracy based on the results of follow-up survey. 26 patients of COVID-19 with negative RT-PCR reports were reported as positive by ddPCR. The sensitivity, specificity, PPV, NPV, negative likelihood ratio (NLR) and accuracy were improved from 40% (95% CI 27-55%), 100% (95% CI 54-100%), 100%, 16% (95% CI 13-19%), 0.6 (95% CI 0.48-0.75) and 47% (95% CI 33-60%) for RT-PCR to 94% (95% CI 83-99%), 100% (95% CI 48-100%), 100%, 63% (95% CI 36-83%), 0.06 (95% CI 0.02-0.18), and 95% (95% CI 84-99%) for ddPCR, respectively. Moreover, 6/14 (42.9%) convalescents were detected as positive by ddPCR at 5-12 days post discharge. Overall, ddPCR shows superiority for clinical diagnosis of SARS-CoV-2 to reduce the false negative reports, which could be a powerful complement to the RT-PCR.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Coronavirus Infections
/
Real-Time Polymerase Chain Reaction
/
Betacoronavirus
Type of study:
Cohort study
/
Diagnostic study
/
Observational study
/
Prognostic study
Topics:
Long Covid
Limits:
Humans
Language:
English
Journal:
Emerg Microbes Infect
Year:
2020
Document Type:
Article
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