ArticleAnnals of laboratory medicine2017
Performance Evaluation of the PowerChek MERS (upE & ORF1a) Real-Time PCR Kit for the Detection of Middle East Respiratory Syndrome Coronavirus RNA.
Article in Annals of laboratory medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Low Prevalence of Middle East Respiratory Syndrome Coronavirus Infection in Camel-Exposed Patients Presenting with Respiratory Symptoms in Northern Kenya.The American journal of tropical medicine and hygiene · 2025Article
- Micro/nanotechnology-inspired rapid diagnosis of respiratory infectious diseases.Biomedical engineering letters · 2021Review
- SARS-CoV, MERS-CoV and SARS-CoV-2: A Diagnostic Challenge.Measurement : journal of the International Measurement Confederation · 2021Article
- Diagnostic Techniques for COVID-19: A Mini-review of Early Diagnostic Methods.Journal of analysis and testing · 2021Review
- Clinical Characteristics, Diagnosis, and Treatment of Major Coronavirus Outbreaks.Frontiers in medicine · 2020Review
- Article
- Evaluation of visual triage for screening of Middle East respiratory syndrome coronavirus patients.New microbes and new infections · 2018Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMolecular detection of Middle East respiratory syndrome coronavirus (MERS-CoV) using real-time reverse transcription (rRT)-PCR assays is the method of choice for diagnosis of MERS. We evaluated the performance of the PowerChek MERS (upE & ORF1a) real-time PCR Kit (PowerChek MERS assay; Kogene Biotech, Korea) a one-step rRT-PCR assay for the qualitative detection of MERS-CoV.
methodsWe evaluated PowerChek MERS assay performance in comparison with nested RT-PCR and sequencing of the RNA-dependent RNA polymerase (RdRp) and N genes. To evaluate diagnostic sensitivity and specificity, 100 clinical specimens (50 positive and 50 negative for MERS-CoV) were simultaneously tested by using the PowerChek MERS and sequencing assays. Assay performance, including limit of detection and precision, was evaluated in vitro by using MERS-CoV RNA transcripts. Analytical specificity was evaluated with a diverse collection of 16 respiratory virus-positive clinical specimens and 14 respiratory bacterial isolates.
resultsThe 95% limits of detection of the PowerChek MERS assay for the upE and the open rading frame (ORF)1a were 16.2 copies/μL and 8.2 copies/μL, respectively. No cross-reactivity was observed. The diagnostic sensitivity and specificity of the PowerChek MERS assay were both 100% (95% confidence interval, 91.1-100%).
conclusionsThe PowerChek MERS assay is a straightforward and accurate assay for detecting MERS-CoV RNA. The assay will be a useful tool for the rapid diagnosis of MERS and could prove especially important for MERS outbreak control.
Indexed as
Identifiers
What OpenQuestion holds
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.