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Record W4386305115 · doi:10.1161/atvbaha.123.318781

New Therapeutic Targets for the Prevention and Treatment of Venous Thromboembolism With a Focus on Factor XI Inhibitors

2023· review· en· W4386305115 on OpenAlexafffund
Noel Chan, Jeffrey I. Weitz

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2023
Typereview
Languageen
FieldMedicine
TopicCoagulation, Bradykinin, Polyphosphates, and Angioedema
Canadian institutionsThrombosis and Atherosclerosis Research InstituteMcMaster UniversityPopulation Health Research Institute
FundersServierCanadian Institutes of Health ResearchRegeneron PharmaceuticalsHeart and Stroke Foundation of CanadaAlnylam PharmaceuticalsAlexion PharmaceuticalsDaiichi Sankyo EuropeBristol-Myers Squibb
KeywordsVenous thromboembolismMedicineIntensive care medicineThrombosisSurgery

Abstract

fetched live from OpenAlex

FXI (factor XI) and FXII (factor XII) have emerged as targets for new anticoagulants that have the potential to be both more efficacious and safer than the currently available direct oral anticoagulants for the prevention and treatment of venous thromboembolism. In this review, we discuss the role of FXI and FXII in the pathogenesis of venous thromboembolism, explain why FXI is a better target, and explain why FXI inhibitors have potential advantages over currently available anticoagulants. Finally, we describe the FXI inhibitors under development and discuss their potential to address unmet needs in venous thromboembolism management.

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 score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.114
GPT teacher head0.356
Teacher spread0.242 · 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

Citations28
Published2023
Admission routes2
Has abstractyes

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