ReviewFrontiers in bioengineering and biotechnology2026
CRISPR-based point-of-care diagnostics for viral hepatitis: from molecular design to clinical implementation.
Review in Frontiers in bioengineering and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Timely etiological diagnosis of viral hepatitis is essential for surveillance, treatment initiation, linkage to care, and elimination efforts. In resource-limited settings, however, diagnostic pathways are frequently disrupted by centralized nucleic acid testing, specimen-transport requirements, delayed reporting, and loss to follow-up. CRISPR-Cas-based point-of-care testing may help shorten these pathways, but its clinical value cannot be judged by analytical sensitivity alone. This review evaluates CRISPR-Cas strategies for detecting hepatitis A, B, C, D, and E viruses by linking molecular design to virus-specific clinical and public-health decisions. We compare target selection, Cas effectors, amplification strategies, readout formats, specimen processing, genotype coverage, clinical validation, and implementation feasibility. For each virus, the evidence is evaluated in relation to the principal diagnostic need, the potential contribution of CRISPR-Cas, the maturity of the available evidence, and the remaining requirements for deployment. Current evidence is most advanced for HBV and HCV, whereas HAV, HDV, and HEV applications remain less developed or more context dependent. Future platforms should prioritize clinically meaningful detection thresholds, closed-tube sample-to-answer workflows, internal controls, genotype-diverse validation, reagent stability, non-expert usability, and transparent pathway-level cost evaluation.
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Registered trials
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