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Antiphospholipid syndrome

2013· review· en· W4239987606 on OpenAlexaff
Wendy Lim

Bibliographic record

VenueHematology · 2013
Typereview
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineAntiphospholipid syndromeThrombosisCatastrophic antiphospholipid syndromeLupus anticoagulantAntithromboticInternal medicineAnticoagulantPregnancyImmunology

Abstract

fetched live from OpenAlex

The antiphospholipid syndrome (APS) is defined by venous or arterial thrombosis and/or pregnancy morbidity in patients with persistent presence of antiphospholipid antibodies (aPLs). Catastrophic APS is the most severe form of APS, which is associated with rapid development of microvascular thrombosis resulting in multiorgan failure in patients with aPLs. Patients with APS and catastrophic APS are recognized to have a high risk of recurrent thrombosis that can occur despite anticoagulant therapy. Although antithrombotic therapy remains the mainstay of treatment, bleeding manifestations can complicate management and contribute to increased morbidity. Patients with persistently elevated aPL levels, particularly those who exhibit positive testing for lupus anticoagulant, anticardiolipin antibodies, and anti-β2GPI antibodies (triple positivity), appear to be at increased risk for thrombosis and pregnancy complications, whereas isolated positivity for aPLs appears to be associated with low risk. Recognizing that patients with APS have different thrombotic risk profiles may assist clinicians in assessing the risks and benefits of anticoagulation. The optimal type, intensity, and duration of anticoagulation in the treatment of APS remain controversial, particularly for arterial thrombosis and recurrent thrombosis. Future studies that delineate thrombotic risk in APS and evaluate current and novel anticoagulants as well as nonanticoagulant therapies are required.

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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.004

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 head0.085
GPT teacher head0.389
Teacher spread0.305 · 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

Citations100
Published2013
Admission routes1
Has abstractyes

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