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Record W2296363428 · doi:10.1160/th15-11-0882

Vorapaxar and diplopia: Possible off-target PAR-receptor mismodulation

2016· review· en· W2296363428 on OpenAlexaff
Seth D. Fortmann, Sunil V. Rao, Jean-François Tanguay, Marie Lordkipanidzé, Daniel F. Hanley, Mehmet Mustafa Can, Moo Hyun Kim, Thomas A. Marciniak, Victor L. Serebruany

Bibliographic record

VenueThrombosis and Haemostasis · 2016
Typereview
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsDiplopiaMedicineAspirinClopidogrelPlaceboAdverse effectCardiologyInternal medicineSurgeryPathology

Abstract

fetched live from OpenAlex

Vorapaxar, a novel antiplatelet thrombin PAR-1 inhibitor, has been evaluated in the successful TRA2P trial and the failed TRACER trial. The drug is currently approved for post myocardial infarction and peripheral artery disease indications with concomitant use of clopidogrel and/or aspirin. The FDA ruled that the vorapaxar safety profile is acceptable. However, both trials revealed excess diplopia (double vision) usually reversible after vorapaxar. The diplopia risk appears to be small (about 1 extra case per 1,000 treated subjects), but real. Overall, there were 10 placebo and 34 vorapaxar diplopia cases (p=0.018) consistent for TRACER (2 vs 13 cases; p=0.010) and for TRA2P (8 vs 21 cases; p=0.018). Hence, we review the FDA-confirmed evidence and discuss potential causes and implications of such a surprising adverse association, which may be related to off-target PAR receptor mismodulation in the eye.

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)0.001
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0010.001
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 head0.064
GPT teacher head0.345
Teacher spread0.281 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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