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Record W2795867865 · doi:10.1111/1756-185x.13283

Diagnosis and management of <scp>ADA</scp>2 deficient polyarteritis nodosa

2018· review· en· W2795867865 on OpenAlexaff
Andrea Human, Christian Pagnoux

Bibliographic record

VenueInternational Journal of Rheumatic Diseases · 2018
Typereview
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsMount Sinai HospitalBC Children's Hospital
Fundersnot available
KeywordsPolyarteritis nodosaMedicineHypogammaglobulinemiaPhenotypeRashDiseasePathogenesisInflammationSystemic inflammationDermatologyImmunologyVasculitisGenePathologyGeneticsBiologyAntibody

Abstract

fetched live from OpenAlex

Deficiency of ADA2 (DADA2) is a recently described systemic inflammatory vasculopathy caused by mutations in the CERC1 gene that often, but not always, clinically resembles polyarteritis nodosa (PAN). The condition was originally characterized by livedoid rash, systemic inflammation, variable hypogammaglobulinemia, and early-onset stroke. The phenotypic spectrum has expanded to include patients with immunodeficiency syndromes and bone marrow dysfunction, which are not typical features of PAN. Exploration into the pathogenesis and treatment options of DADA2 has added to our understanding of this condition, but more studies are needed. The purpose of this article is to review the various clinical phenotypes of DADA2, and raise awareness among rheumatologists to consider DADA2 when evaluating patients presenting with PAN-like disease.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.961
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.026
GPT teacher head0.323
Teacher spread0.297 · 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 designOther design
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

Citations36
Published2018
Admission routes1
Has abstractyes

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