ReviewReviews in medical virology2022
Biomarker based biosensors: An opportunity for diagnosis of COVID-19.
Review in Reviews in medical virology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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
7 citing papers in PubMed, 18 citations in OpenAlex.
- A Review of Respiratory Infection Caused by the Human Metapneumovirus: Occurrence, Epidemiology, Pathogenesis, Public Health Outcomes, and Intervention Strategies.Health science reports · 2026Article
- Identification of biomarkers and mechanisms associated with palmitoylation in acute kidney injury using transcriptome and single cell data.Scientific reports · 2025Article
- Biosensor Technologies for Water Quality: Detection of Emerging Contaminants and Pathogens.Biosensors · 2025Review
- End-to-end dataflow engineering framework of honey manufacturing from intermediates to process by TAS1R2@AuNPs/SPCE biosensor coupled with quality transfer principle.Fundamental research · 2025Article
- Therapeutic potential and possible mechanisms of ginseng for depression associated with COVID-19.Inflammopharmacology · 2024Review
- Advances in Biosensing Technologies for Diagnosis of COVID-19.Biosensors · 2022Review
- Biomarker based biosensors: An opportunity for diagnosis of COVID-19.Reviews in medical virology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early diagnosis and treatment of diseases are crucial research areas of human health. For early diagnosis, one method that has proven efficient is the detection of biomarkers which can provide real-time and accurate biological information. Most biomarker detection is currently carried out at localised dedicated laboratories using large and automated analysers, increasing waiting time and costs. Smaller, faster, and cheaper devices could potentially replace these time-consuming laboratory analyses and make analytical results available as point-of-care diagnostics. Innovative biosensor-based strategies could allow biomarkers to be tested reliably in a decentralised setting. Early diagnosis of COVID-19 patients has a key role in order to use quarantine and treatment strategies in a timely manner. Raised levels of several biomarkers in COVID-19 patients are associated with respiratory infections or dysfunction of various organs. Through clinical studies of COVID-19 patient biomarkers such as ferritin, Interleukins, albumin and …are found to reveals significant differences in their excretion ranges from healthy patients and patients with SARS-CoV-2, in addition to the development of biomarkers based biosensor such as stated biomarkers can be used and to investigate more specific biomarkers further proteomic analysis can be performed. This review presents several biomarker alterations in COVID-19 patients such as salivary, circulatory, coagulation, cardiovascular, renal, liver, C-reactive protein (CRP), immunological and inflammatory biomarkers. Also, biomarker sensors based on electrochemical, optical, and lateral flow characteristics which have potential applications for SARS-COV-2 in the recent COVID-19 pandemic, will be discussed.
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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.