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Record W4296955672 · doi:10.4081/monaldi.2022.2414

Varicella zoster virus and cardiovascular diseases

2022· review· en· W4296955672 on OpenAlexaff
Angelica Cersosimo, Mauro Riccardi, Ludovica Amore, Giuliana Cimino, Gianmarco Arabia, Marco Metra, Enrico Vizzardi

Bibliographic record

VenueMonaldi Archives for Chest Disease · 2022
Typereview
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsVaricella zoster virusMedicineVirusDiseaseImmunologyArteritisPopulationVirologyPathology

Abstract

fetched live from OpenAlex

Varicella zoster virus (VZV) is a Herpesviridae family double-stranded DNA virus that only affects humans. The first clinical manifestation appears to be varicella, typical of childhood. VZV, on the other hand, becomes latent in ganglion neurons throughout the neuroaxis after primary infection. The VZV reactivates and travels along peripheral nerve fibers in the elderly and immunocompromised individuals, resulting in Zoster. It can, however, spread centrally and infect cerebral and extracranial arteries, resulting in vasculopathy, which can lead to transient ischemic attacks, strokes, aneurysms, cavernous sinus thrombosis, giant cell arteritis, and granulomatous aortitis. Although the mechanisms of virus-induced pathological vascular remodeling are not fully understood, recent research indicates that inflammation and dysregulation of ligand-1 programmed death play a significant role. Few studies, on the other hand, have looked into the role of VZV in cardiovascular disease. As a result, the purpose of this review is to examine the relationship between VZV and cardiovascular disease, the efficacy of the vaccine as a protective mechanism, and the target population of heart disease patients who could benefit from vaccination.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.315
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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