Evidence map›Paper›PMID 35227385›Full record

ArticleAnalytica chimica acta2022

Importance of sample input volume for accurate SARS-CoV-2 qPCR testing.

Yugan He, Tie Xie, Qihang Tu, Yigang Tong

Abstract read
In one paragraph

Article in Analytica chimica acta, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
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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

4 authors.

Yugan HeBeijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, PR China; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, PR China.
Tie XieBeijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, PR China; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, PR China.
Qihang TuCollege of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, PR China.
Yigang TongBeijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing, 100029, PR China; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, PR China. Electronic address: tongyigang@mail.buct.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nucleic acid testing is the most widely used detection method for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the coronavirus disease 2019 (COVID-19) pandemic. Currently, a number of COVID-19 real-time quantitative reverse transcription PCR (qPCR) kits with high sensitivity and specificity are available for SARS-CoV-2 testing. However, these qPCR assays are not always reliable in detecting low viral load samples (Ct-value ≥ 35), resulting in inconclusive or false-negative results. Here, we used a Poisson distribution to illustrate the inconsistent performance of qPCR tests in detecting low viral load samples. From this, we concluded that the false-negative outcomes resulted from the random occurrences of sampling zero target molecules in a single test, and the probability to sample zero target molecules in one test decreased significantly with increasing purified RNA or initial sample input volume. At a given RNA concentration of 0.5 copy/μL, the probability of sampling zero RNA molecules decreased from 36.79% to close to 0.67% after increasing the RNA input volume from 2 to 10 μL. A SARS-CoV-2 qPCR assay with an LOD of 300 copies/mL was used to validate the improved consistency of the qPCR tests. We found that the false-negative qPCR results of clinical COVID-19 samples with a Ct ≥ 35 decreased by 50% after increasing the input of purified RNA from 2 to 10 μL. The consistency, accuracy, and robustness of nucleic acid testing for SARS-CoV-2 samples with low viral loads can be improved by increasing the sample input volume.

Indexed as

COVID-19SARS-CoV-2COVID-19 TestingHumansPandemicsRNA, ViralSensitivity and SpecificityRNA, ViralNucleic acid testingPoisson distributionSample inputSARS-CoV-2

Identifiers

PMID35227385
PMCPMC8820412

What OpenQuestion holds

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Registered trials

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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.