ReviewJournal of biological engineering2024
Current advances in Hepatitis C diagnostics.
Review in Journal of biological engineering, 2024. 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
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
7 citing papers in PubMed.
- Missed confirmatory HCV RNA testing in anti-HCV-reactive patients and the role of reflex testing in improving completion of the hepatitis C diagnostic care cascade: a laboratory-based retrospective study.BMC infectious diseases · 2026Observational
- Native-like soluble E1E2 glycoprotein heterodimers on self-assembling protein nanoparticles for hepatitis C virus vaccine design.Nature communications · 2026Article
- Article
- OraQuick hepatitis C virus self-test: A new frontier in hepatitis C screening.World journal of virology · 2025Article
- Pathogenesis, prevention, and therapeutic advances in hepatitis B, C, and D.Virology journal · 2025Review
- A review of historical landmarks and pioneering technologies for the diagnosis of Hepatitis C Virus (HCV).European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2025Review
- Predicting hepatitis C infection via machine learning.American journal of translational research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nearly 60 million people worldwide are infected with Hepatitis C Virus (HCV), a bloodborne pathogen which leads to liver cirrhosis and increases the risk of hepatocellular carcinoma. Those with limited access to healthcare resources, such as injection drug users and people in low- and middle-income countries, carry the highest burden. The current diagnostic algorithm for HCV is slow and costly, leading to a significant barrier in diagnosis and treatment for those most at risk from HCV. There remains no available vaccine for HCV, and infection is often asymptomatic until significant cirrhosis has occurred, which makes screening incredibly important to prevent liver damage and transmission. Recent investigation has sought to address these issues through improvements in various aspects of the diagnostic procedure, using methods such as isothermal amplification techniques for viral RNA amplification, the use of viral protein as an analyte, and the incorporation of streamlined, self-contained testing systems to reduce administrative skill requirements. This review provides a comprehensive overview of current commercial standards and novel improvements in HCV diagnostics, as well as a framework for future integration of these improvements to develop a one-step diagnostic that meets the needs of those most affected.
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.