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Record W2512686635 · doi:10.1016/j.amjmed.2016.06.009

Preclinical and Clinical Data for Factor Xa and “Universal” Reversal Agents

2016· review· en· W2512686635 on OpenAlexfundno aff
Truman J. Milling, Scott Kaatz

Bibliographic record

VenueThe American Journal of Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsnot available
FundersCSL BehringMcMaster UniversityPfizerDaiichi Sankyo EuropeBristol-Myers SquibbNational Heart, Lung, and Blood InstituteBoehringer Ingelheim
KeywordsMedicineClinical trialStroke (engine)Atrial fibrillationIntensive care medicineVenous thromboembolismClotting factorRivaroxabanPharmacologyInternal medicineWarfarinThrombosis

Abstract

fetched live from OpenAlex

Oral Factor Xa (FXa) inhibitors, a growing class of direct-acting anticoagulants, are frequently used to prevent stroke and systemic embolism in patients with atrial fibrillation and to prevent and treat venous thromboembolism. These drugs reduce the risk of clotting at the expense of increasing the risk of bleeding, and currently they have no specific reversal agent. However, andexanet alfa, a recombinant modified FXa decoy molecule, is in a late-phase clinical trial in bleeding patients, and ciraparantag, a small molecule that appears to reverse many anticoagulants including the FXa inhibitors, is in development. This review summarizes the published data to date on both drugs, which have the potential to change the management approach to patients with FXa inhibitor-associated major hemorrhage.

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)0.002
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 score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
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)0.0080.002

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 head0.450
GPT teacher head0.548
Teacher spread0.098 · 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

Citations24
Published2016
Admission routes1
Has abstractyes

Explore more

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