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Record W1580628800 · doi:10.4212/cjhp.v61i4.65

Possible Enhancement of the Effect of Warfarin Secondary to Oral Prednisone Therapy

2008· article· en· W1580628800 on OpenAlexaffvenue
Jeff Nagge, Jennifer Sebben, John Yee

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2008
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacovigilance and Adverse Drug Reactions
Canadian institutionsCentre for Family Medicine
Fundersnot available
KeywordsWarfarinMedicinePrednisoneMethylprednisoloneDrugIntensive care medicineInternal medicinePharmacologyAtrial fibrillation

Abstract

fetched live from OpenAlex

Alarge number of medications have been reported to either increase or decrease the effect of warfarin on the international normalized ratio (INR).1 Therefore, knowledge of medications that may interact with warfarin is essential to ensure safe and effective use of this drug. Patients taking warfarin should undergo more frequent testing of INR upon introduction of new medications that may interact with warfarin. In a recent systematic review of medications and foods that may interact with warfarin, oral corticosteroids were not listed as having clinically significant interactions. 1 In fact, interactions between methylprednisolone and warfarin were described as “highly improbable”.1 We report here a clinically significant increase in INR associated with the initiation of oral prednisone therapy in a patient whose condition had previously been stabilized with warfarin 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 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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.066
GPT teacher head0.387
Teacher spread0.321 · 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 designCase report
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

Citations0
Published2008
Admission routes2
Has abstractyes

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