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Record W3112696609 · doi:10.1016/j.cjco.2020.11.021

Implications of the Antiplatelet Therapy Gap Left With Discontinuation of Prasugrel in Canada

2020· article· en· W3112696609 on OpenAlexafffundabout
Marie Lordkipanidzé, Guillaume Marquis‐Gravel, Jean‐François Tanguay, Shamir R. Mehta, Derek So

Bibliographic record

VenueCJC Open · 2020
Typearticle
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsMcMaster UniversityUniversité de MontréalUniversity of OttawaHamilton Health SciencesMontreal Heart Institute
FundersLEO Pharma Research FoundationUniversité de MontréalHeart and Stroke Foundation of CanadaRoche
KeywordsPrasugrelMedicineClopidogrelDiscontinuationTicagrelorP2Y12GynecologyInternal medicineAspirin

Abstract

fetched live from OpenAlex

BACKGROUND: The current Canadian Cardiovascular Society antiplatelet therapy guidelines recommend the use of ticagrelor or prasugrel over clopidogrel as first-line platelet P2Y12 receptor antagonists for treatment of moderate- to high-risk acute coronary syndromes. Recently, Effient (prasugrel [Eli Lilly Canada Inc, Toronto, Canada]) was discontinued by its distributor in Canada. METHODS: Five members of the Canadian Cardiovascular Society antiplatelet therapy 2018 guidelines committee undertook an independent, evidence-based review to outline patients for whom prasugrel should be the optimal P2Y12 agent and discuss alternative strategies to consider without prasugrel. RESULTS: Several clinical scenarios where prasugrel should be indicated are identified and discussed. Considerations to be undertaken for alternative therapies are summarized, including a review of national and international guidelines for de-escalation of P2Y12 receptor antagonists. CONCLUSIONS: The discontinuation of prasugrel poses a challenge for clinicians. Clinicians must consider key factors in determining the best alternate therapy.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.028
GPT teacher head0.263
Teacher spread0.234 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations6
Published2020
Admission routes3
Has abstractyes

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