ArticleJournal of clinical microbiology2021
Portable RT-PCR System: a Rapid and Scalable Diagnostic Tool for COVID-19 Testing.
Article in Journal of clinical microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed.
- Comparative analysis of laboratory-based and portable qPCR platforms: CFX, MIC, and Biomeme Franklin for African swine fever and avian influenza detection.BMC veterinary research · 2026Article
- Laboratory Validation of a Fully Automated Point-of-Care Device for High-Order Multiplexing Real-Time PCR Detection of Respiratory Pathogens.Diagnostics (Basel, Switzerland) · 2025Article
- CoVSense: Ultrasensitive Nucleocapsid Antigen Immunosensor for Rapid Clinical Detection of Wildtype and Variant SARS-CoV-2.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- A Systematic Review and Meta-Analysis Comparing the Diagnostic Accuracy Tests of COVID-19.Diagnostics (Basel, Switzerland) · 2023Review
- Environmental DNA in human and veterinary parasitology - Current applications and future prospects for monitoring and control.Food and waterborne parasitology · 2022Article
- Diagnostic assay and technology advancement for detecting SARS-CoV-2 infections causing the COVID-19 pandemic.Analytical and bioanalytical chemistry · 2022Review
- Development, testing and validation of a SARS-CoV-2 multiplex panel for detection of the five major variants of concern on a portable PCR platform.Frontiers in public health · 2022Article
- Comparison of the Performance of 24 Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Assays in the Diagnosis of Coronavirus Disease 2019 Patients.Frontiers in microbiology · 2022Article
- Strategies for the preparation of non-amplified and amplified genomic dengue gene samples for electrochemical DNA biosensing applications.RSC advances · 2021Article
- Management of COVID-19 Patients in the Emergency Department.Journal of personalized medicine · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Combating the ongoing coronavirus disease 2019 (COVID-19) pandemic demands accurate, rapid, and point-of-care testing with fast results to triage cases for isolation and treatment. The current testing relies on reverse transcriptase PCR (RT-PCR), which is routinely performed in well-equipped laboratories by trained professionals at specific locations. However, during busy periods, high numbers of samples queued for testing can delay the test results, impacting efforts to reduce the infection risk. Besides, the absence of well-established laboratories at remote sites and low-resourced environments can contribute to a silent spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). These reasons compel the need to accommodate point-of-care testing for COVID-19 that meets the ASSURED criteria (
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Registered trials
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.