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Record W4387244462 · doi:10.1016/j.atssr.2023.09.014

Anticoagulation of HeartMate 3 Left Ventricular Assist Device With Apixaban

2023· article· en· W4387244462 on OpenAlexaff
Emily Cowley, June Chen, Hazal E. Babadagli, Qiang Fu, Jennifer Conway, Holger Buchholz

Bibliographic record

VenueAnnals of Thoracic Surgery Short Reports · 2023
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsStollery Children's HospitalAlberta HealthUniversity of Alberta HospitalAlberta Hospital EdmontonAlberta Health Services
Fundersnot available
KeywordsApixabanCardiologyInternal medicineVentricular assist deviceMedicineHeart failureWarfarinAtrial fibrillationRivaroxaban

Abstract

fetched live from OpenAlex

We report a case of a 56-year-old man requiring a HeartMate 3 after a myocardial infarction and limited recovery on a temporary ventricular assist device. Because of several gastrointestinal bleeding complications and nonadherence, his antithrombotic therapy was switched from warfarin and aspirin to apixaban 5 mg twice daily. We also determined several peak anti-factor Xa levels for ongoing monitoring. Direct oral anticoagulants may be an option for the prevention of pump thrombosis in patients who are unable to tolerate or refuse 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 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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.838

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.072
GPT teacher head0.330
Teacher spread0.257 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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