Evidence map›Paper›PMID 37378785›Full record

ArticleAdvances in experimental medicine and biology2023

Rapid Detection of SARS-CoV-2 Variants of Concern by Genomic Surveillance Techniques.

Paul C Guest, Steve F C Hawkins, Hassan Rahmoune

Abstract read
PubMed Publisher
In one paragraph

Article in Advances in experimental medicine and biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Paul C GuestLaboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil.
Steve F C HawkinsMeridian Bioscience, Unit 16, The Edge Business Centre, London, UK.
Hassan RahmouneDepartment of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This chapter describes the application of genomic, transcriptomic, proteomic, and metabolomic methods in the study of SARS-CoV-2 variants of concern. We also describe the important role of machine learning tools to identify the most significant biomarker signatures and discuss the latest point-of-care devices that can be used to translate these findings to the physician's office or to bedside care. The main emphasis is placed on increasing our diagnostic capacity and predictability of disease outcomes to guide the most appropriate treatment strategies.

Indexed as

COVID-19SARS-CoV-2GenomicsHumansProteomicsCOVID-19DiagnosisDisease managementLab-on-a-chipPOCPoint-of-careSARS-COV-2

Identifiers

PMID37378785

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.