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Record W4405109054 · doi:10.1182/hematology.2024000666

DOACs: role of anti-Xa and drug level monitoring

2024· review· en· W4405109054 on OpenAlex
Siraj Mithoowani, Deborah Siegal

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHematology · 2024
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsOttawa HospitalUniversity of OttawaMcMaster University
Fundersnot available
KeywordsMedicineDrugPartial thromboplastin timeTherapeutic drug monitoringDabigatranIntensive care medicineCoagulationAnticoagulantInternal medicinePharmacologyWarfarinAtrial fibrillation

Abstract

fetched live from OpenAlex

Direct oral anticoagulants (DOACs) do not require routine monitoring of anticoagulant effect, but measuring DOAC activity may be desirable in specific circumstances to detect whether clinically significant DOAC levels are present (eg, prior to urgent surgery) or to assess whether drug levels are excessively high or excessively low in at-risk patients (eg, after malabsorptive gastrointestinal surgery). Routine coagulation tests, including the international normalized ratio (INR) or activated partial thromboplastin time (aPTT), cannot accurately quantify drug levels but may provide a qualitative assessment of DOAC activity when considering the estimated time to drug clearance based on timing of last drug ingestion and renal and hepatic function. Drug-specific chromogenic and clot-based assays can quantify drug levels but they are not universally available and do not have established therapeutic ranges. In this review, we discuss our approach to measuring DOAC drug levels, including patient selection, interpretation of coagulation testing, and how measurement may inform clinical decision-making in specific scenarios.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.166
GPT teacher head0.423
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