Evidence map›Paper›PMID 39749520›Full record

ReviewClinical chemistry2025

Virus Evolution in Prolonged Infections of Immunocompromised Individuals.

Zoe Raglow, Adam S Lauring

Abstract readReview
In one paragraph

Review in Clinical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
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

2 authors.

Zoe RaglowDivision of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.
Adam S LauringDivision of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0003-2906-8335

Funding

Evolution and Transmission of Influenza Virus in Natural Human InfectionR01AI148371 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LAURING, ADAM, MARTIN, EMILY TOTH · 2020 to 2024
$3.6M
NCIRD CDC HHS U01 IP001193NIAID NIH HHS R01 AI148371
6 · The paper itself

Abstract

backgroundMany viruses can cause persistent infection and/or viral shedding in immunocompromised hosts. This is a well-described occurrence not only with SARS-CoV-2 but for many other viruses as well. Understanding how viruses evolve and mutate in these patients and the global impact of this phenomenon is critical as the immunocompromised population expands. CONTENT: In this review, we provide an overview of populations at risk for prolonged viral shedding, clinical manifestations of persistent viral infection, and methods of assessing viral evolution. We then review the literature on viral evolution in immunocompromised patients across an array of RNA viruses, including SARS-CoV-2, norovirus, influenza, and poliovirus, and discuss the global implications of persistent viral infections in these hosts. SUMMARY: There is significant evidence for accelerated viral evolution and accumulation of mutations in antigenic sites in immunocompromised hosts across many viral pathogens. However, the implications of this phenomenon are not clear; while there are rare reports of transmission of these variants, they have not clearly been shown to predict disease outbreaks or have significant global relevance. Emerging methods including wastewater monitoring may provide a more sophisticated understanding of the impact of variants that evolve in immunocompromised hosts on the wider host population.

Indexed as

Immunocompromised HostSARS-CoV-2COVID-19Evolution, MolecularHumansMutationVirus DiseasesVirus Shedding

Identifiers

PMID39749520
PMCPMC11822857

What OpenQuestion holds

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Registered trials

None linked

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.