Evidence map›Paper›PMID 41474328›Full record

ArticleJournal of clinical microbiology2026

Challenges in accurate HDV RNA quantification: inter-assay variability and the impact of thermal shock.

Felipe Pérez-García, Ana Virseda-Berdices, Carlos Pita-Martínez, Mario Muñoz Monte, Daniel Sepúlveda-Crespo, Helena Codina, Roberto Alonso, Lara Mesones, Sandra Rodrigo, Juan Macías and 4 more

Abstract readEvaluation StudyComparative Study
In one paragraph

Article in Journal of clinical microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Felipe Pérez-GarcíaServicio de Microbiología Clínica, Hospital Universitario Príncipe de Asturias, Madrid, Spain.ORCID 0000-0002-4885-4334
Ana Virseda-BerdicesCentro de Investigación Biomédica en Red en Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.
Carlos Pita-MartínezUnidad de Infección Viral e Inmunidad, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain.
Mario Muñoz MonteServicio de Microbiología Clínica, Hospital Universitario Príncipe de Asturias, Madrid, Spain.
Daniel Sepúlveda-CrespoCentro de Investigación Biomédica en Red en Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.ORCID 0000-0002-8053-6045
Helena CodinaCentro de Investigación Biomédica en Red en Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.
Roberto AlonsoServicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, Madrid, Spain.ORCID 0000-0002-0516-6371
Lara MesonesServicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, Madrid, Spain.
Sandra RodrigoServicio de Microbiología Clínica y Enfermedades Infecciosas, Hospital General Universitario Gregorio Marañón, Madrid, Spain.
Juan MacíasCentro de Investigación Biomédica en Red en Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.
Luis Miguel RealCentro de Investigación Biomédica en Red en Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.ORCID 0000-0003-4932-7429
Juan Cuadros-GonzálezServicio de Microbiología Clínica, Hospital Universitario Príncipe de Asturias, Madrid, Spain.
Isidoro Martínez *Centro de Investigación Biomédica en Red en Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.ORCID 0000-0002-9949-9264
Salvador Resino *Centro de Investigación Biomédica en Red en Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.ORCID 0000-0001-8783-0450

Funding

Centro de Investigación en Red en Enfermedades Infecciosas CB21/13/00044European Society of Clinical Microbiology and Infectious Diseases ESCMIDRG17142Fundación para la Investigación Biomédica del Hospital Universitario Príncipe de Asturias VHD-HUPAInstituto de Salud Carlos III CP23CIII/00004Instituto de Salud Carlos III PI19CIII/00009Instituto de Salud Carlos III PI20CIII/00004
6 · The paper itself

Abstract

Quantitative RT-PCR (qRT-PCR) is essential for monitoring hepatitis delta virus (HDV) RNA, yet assays lack standardization. We aimed to evaluate the performance of three qRT-PCR assays and to assess the impact of a pre-analytical thermal shock procedure. We conducted a comparative study using 206 samples (106 with anti-HDV antibodies and 100 anti-HDV-negative as a control group), which were tested in parallel with three qRT-PCR assays: Vircell, Certest, and Altona. Performance was evaluated for inter-assay agreement (kappa index), quantitative correlation (R²), and bias (Bland-Altman). Altona detected 56 HDV-RNA positive samples, whereas Vircell and Certest detected 55 positive samples. Inter-assay agreement was perfect comparing Vircell vs Certest (agreement = 100%, к = 1.000) and almost perfect comparing Altona with both Vircell and Certest (agreement = 99.5%, к = 0.988). Quantitatively, Vircell and Certest assays showed relevant systematic biases compared to Altona, overestimating viral loads by approximately 0.24 log

Indexed as

Hepatitis DHepatitis Delta VirusReal-Time Polymerase Chain ReactionRNA, ViralViral LoadHumansReproducibility of ResultsSensitivity and SpecificityRNA, Viralhepatitis D virusinter-assay variabilityqRT-PCRthermal shockviral load

Identifiers

PMID41474328
PMCPMC12892981

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Registered trials

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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.