MétaCan
Menu
Back to cohort
Record W2035253720 · doi:10.1155/2012/723062

The Link between Hypersensitivity Syndrome Reaction Development and Human Herpes Virus-6 Reactivation

2012· article· en· W2035253720 on OpenAlexaff
Joshua C. Pritchett, Radu M. Nanau, Manuela G. Neuman

Bibliographic record

VenueInternational Journal of Hepatology · 2012
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsUniversity of Toronto
FundersHHV-6 Foundation
KeywordsMedicineVirologyHypersensitivity reactionVirusLink (geometry)ImmunologyComputer science

Abstract

fetched live from OpenAlex

Background. There are challenges in the clinical diagnosis of drug-induced injury and in obtaining information on the reactivation of human herpes viruses (HHV) during idiosyncratic adverse drug reactions. Objectives. (i) To develop a unified list of drugs incriminated in drug-induced hepatotoxicity and severe cutaneous reactions, in which drug hypersensitivity leads to HHV-6 reactivation and further complication of therapy and recovery and (ii) to supplement the already available data on reporting frequencies of liver- or skin-induced cases with knowledge of individual case reports, including HHV-6 reactivation and briefly introducing chromosomally integrated HHV-6. Data Sources and Extraction. Drugs identified as causes of (i) idiosyncratic reactions, (ii) drug-induced hypersensitivity, drug-induced hepatotoxicity, acute liver failure, and Stevens-Johnson syndrome, and (iii) human herpes virus reactivation in PubMed since 1997 have been collected and discussed. Results. Data presented in this paper show that HHV-6 reactivation is associated with more severe organ involvement and a prolonged course of disease. Conclusion. This analysis of HHV-6 reactivation associated with drug-induced severe cutaneous reactions and hepatotoxicity will aid in causality assessment and clinical diagnosis of possible life-threatening events and will provide a basis for further patient characterization and therapy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.324
Teacher spread0.287 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations39
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of HepatologySame topicDrug-Induced Adverse ReactionsFrench-language works237,207