MétaCan
Menu
Back to cohort
Record W2997069553 · doi:10.14740/jmc3399

A Case Report of Rivaroxaban-Induced Urticaria and Angioedema With Possible Cross-Reaction to Dabigatran

2019· article· en· W2997069553 on OpenAlexvenueno aff
Tanvi Patil, Christina Ikekwere

Bibliographic record

VenueJournal of Medical Cases · 2019
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAngioedemaDabigatranRivaroxabanAnaphylaxisWarfarinDermatologyDrugAtrial fibrillationAdverse drug reactionAnesthesiaAllergyInternal medicinePharmacologyImmunology

Abstract

fetched live from OpenAlex

Anticoagulants are commonly associated with hemorrhagic complications. However, rare hypersensitivity drug reactions associated with direct oral anticoagulants (DOACs) in form of cutaneous reactions such as urticaria as well as angioedema can have significant burden owing to increase in morbidity and mortality. Angioedema can be allergic, hereditary or idiopathic and can occur in isolation, in combination with urticaria as contributing component of anaphylaxis. With increase in the use of DOACs over warfarin as choice of anticoagulant in the treatment of atrial fibrillation (AF) as well as venous thromboembolism (VTE), recent post marketing surveillance has identified several reports of adverse drug reactions. This case report describes the clinical course of patient being treated for VTE, who experienced rivaroxaban-induced urticaria and angioedema. We further provide evidence for cross-reactivity to dabigatran manifested as significant cutaneous reaction. Patient was transitioned to warfarin with enoxaparin bridge and tolerated it well without any complications.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0040.002
Scholarly communication0.0030.004
Open science0.0020.003
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.035
GPT teacher head0.348
Teacher spread0.313 · 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 designCase report
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

Citations6
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Medical CasesSame topicDrug-Induced Adverse ReactionsFrench-language works237,207