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Record W2116238604 · doi:10.1345/aph.1e179

Moxifloxacin—Warfarin Interaction: A Series of Five Case Reports

2005· article· en· W2116238604 on OpenAlexaff
Dean Elbe, Sandra Chang

Bibliographic record

VenueAnnals of Pharmacotherapy · 2005
Typearticle
Languageen
FieldMedicine
TopicAntibiotics Pharmacokinetics and Efficacy
Canadian institutionsRichmond Hospital
Fundersnot available
KeywordsMedicineMoxifloxacinWarfarinSeries (stratigraphy)Intensive care medicineAtrial fibrillationInternal medicineAntibioticsMicrobiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To report 5 cases of a moxifloxacin-warfarin drug interaction, all resulting in elevated international normalized ratios (INRs) and clinically significant hemorrhage in one case. CASE SUMMARIES: Between January 2002 and January 2004, 4 men and 1 woman (age range 63-92 y) were retrospectively identified as having significantly elevated INR results shortly after being prescribed moxifloxacin with concomitant warfarin therapy. DISCUSSION: This is the second series of case reports describing an interaction between warfarin and moxifloxacin. The current moxifloxacin product monograph indicates this drug has no significant effect on the pharmacokinetics of R- or S-warfarin or the prothrombin time (INR). A moxifloxacin-warfarin interaction probably led to prolonged hospitalization in 2 cases and significant gastrointestinal hemorrhage in one case. In 3 of the 5 cases, a moxifloxacin-warfarin interaction was assessed as probable, and in the remaining 2 cases, a moxifloxacin-warfarin interaction was assessed as possible by use of the Naranjo probability scale. CONCLUSIONS: Healthcare professionals should consider moxifloxacin for the potential to interact with warfarin. Routine, frequent INR monitoring for patients previously stabilized on warfarin during initiation and discontinuation of moxifloxacin may help detect this potential interaction.

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)0.009
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.073
GPT teacher head0.413
Teacher spread0.341 · 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

Citations21
Published2005
Admission routes1
Has abstractyes

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