Evidence map›Paper›PMID 39859446›Full record

ArticleInternational journal of molecular sciences2025

Comparative Analysis of Viral Load Quantification Using Reverse Transcription Polymerase Chain Reaction and Digital Droplet Polymerase Chain Reaction.

Paula Gebe Abreu Cabral, Sávio Bastos de Souza, Raul Ferraz Arruda, Sheila Passos de Figueiredo Cabral, Arícia Leone Evangelista Monteiro de Assis, Yolanda Porto Muniz Martins, Antônio Brazil Viana Junior, Junbiao Chang, Pingsheng Lei, Renato Martins da Silva

Abstract readComparative Study
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Paula Gebe Abreu CabralHigh Complexity Center, Instituto Galzu, Campos dos Goytacazes 28110-000, RJ, Brazil.
Sávio Bastos de SouzaHigh Complexity Center, Instituto Galzu, Campos dos Goytacazes 28110-000, RJ, Brazil.
Raul Ferraz ArrudaHigh Complexity Center, Instituto Galzu, Campos dos Goytacazes 28110-000, RJ, Brazil.
Sheila Passos de Figueiredo CabralHigh Complexity Center, Instituto Galzu, Campos dos Goytacazes 28110-000, RJ, Brazil.
Arícia Leone Evangelista Monteiro de AssisHigh Complexity Center, Instituto Galzu, Campos dos Goytacazes 28110-000, RJ, Brazil.
Yolanda Porto Muniz MartinsHigh Complexity Center, Instituto Galzu, Campos dos Goytacazes 28110-000, RJ, Brazil.
Antônio Brazil Viana JuniorComplexo Hospital Universitário Walter Cantídio da UFC/Ebserh, Fortaleza 60430-372, CE, Brazil.
Junbiao ChangNMPA Key Laboratory for Research and Evaluation of Innovative Drug, Henan Normal University, Xinxiang 453007, China.
Pingsheng LeiInstitute of Material Medical, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China.
Renato Martins da SilvaHigh Complexity Center, Instituto Galzu, Campos dos Goytacazes 28110-000, RJ, Brazil.ORCID 0000-0003-3893-8611

Funding

Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro E-26/211.137/2021HRH Pharmaceutical IGZ1/IGZ2National Council for Scientific and Technological Development 402964/2022-5
6 · The paper itself

Abstract

In the year 2019, a highly virulent coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged, precipitating the outbreak of the illness known as coronavirus disease 2019 (COVID-19). The commonly employed reverse transcription polymerase chain reaction (RT-qPCR) methodology serves to estimate the viral load in each patient's sample by employing a standard curve. However, it is imperative to recognize that this technique exhibits limitations with respect to clinical diagnosis and therapeutic applications, since an advancement of the conventional polymerase chain reaction methods, digital polymerase chain reaction (digital PCR or DDPCR), enables the direct quantification and clonal amplification of nucleic acid strands. The primary divergence between dPCR and traditional PCR resides in their approaches to measuring nucleic acid quantities. In this study, we investigated the viral loads of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) within 461 participants. By employing both RT-qPCR and DDPCR techniques, we established a comparison between the quantification methodologies of the two approaches. Our findings illustrate that the quantification through DDPCR affords a superior means of monitoring viral load within lower respiratory tract samples, thus enhancing the assessment of disease progression, particularly in scenarios characterized by low viral loads.

Indexed as

COVID-19Reverse Transcriptase Polymerase Chain ReactionSARS-CoV-2Viral LoadAdultAgedCOVID-19 Nucleic Acid TestingFemaleHumansMaleMiddle AgedReal-Time Polymerase Chain ReactionRNA, ViralRNA, ViralAZVUDINECOVID-19DDPCRFNCSARS-CoV-2viral load

Identifiers

PMID39859446
PMCPMC11766040

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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.