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Details

Autor(en) / Beteiligte
Titel
Hepatitis C Diagnosis: Simplified Solutions, Predictive Barriers, and Future Promises
Ist Teil von
  • Diagnostics (Basel), 2021-07, Vol.11 (7), p.1253
Ort / Verlag
Switzerland: MDPI AG
Erscheinungsjahr
2021
Quelle
EZB-FREE-00999 freely available EZB journals
Beschreibungen/Notizen
  • The simplification of current hepatitis C diagnostic algorithms and the emergence of digital diagnostic devices will be very crucial to achieving the WHO's set goals of hepatitis C diagnosis (i.e., 90%) by 2030. From the last decade, hepatitis C diagnosis has been revolutionized by the advent and approval of state-of-the-art HCV diagnostic platforms which have been efficiently implemented in high-risk HCV populations in developed nations as well as in some low-to-middle income countries (LMICs) to identify millions of undiagnosed hepatitis C-infected individuals. Point-of-care (POC) rapid diagnostic tests (RDTs; POC-RDTs), RNA reflex testing, hepatitis C self-test assays, and dried blood spot (DBS) sample analysis have been proven their diagnostic worth in real-world clinical experiences both at centralized and decentralized diagnostic settings, in mass hepatitis C screening campaigns, and hard-to-reach aboriginal hepatitis C populations in remote areas. The present review article overviews the significance of current and emerging hepatitis C diagnostic packages to subvert the public health care burden of this 'silent epidemic' worldwide. We also highlight the challenges that remain to be met about the affordability, accessibility, and health system-related barriers to overcome while modulating the hepatitis C care cascade to adopt a 'test and treat' strategy for every hepatitis C-affected individual. We also elaborate some key measures and strategies in terms of policy and progress to be part of hepatitis C care plans to effectively link diagnosis to care cascade for rapid treatment uptake and, consequently, hepatitis C cure.
Sprache
Englisch
Identifikatoren
ISSN: 2075-4418
eISSN: 2075-4418
DOI: 10.3390/diagnostics11071253
Titel-ID: cdi_doaj_primary_oai_doaj_org_article_7e6457f4f86448129a8ed42ad751a32c

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