Argatroban therapy in heparin-induced thrombocytopenia
Bibliographic record
Abstract
INTRODUCTION When heparin-induced thrombocytopenia (HIT) is reasonably suspected, all heparin exposures should be eliminated and an alternative nonheparin anticoagulant expeditiously initiated (Warkentin et al., 2008; Linkins et al., 2012). Alternative anticoagulation is mandated, regardless of whether there is a complicating thrombosis or other ongoing need for anticoagulation, because of the high risk for new clots (Warkentin and Kelton, 1996; Rice, 2004). In the United States, two alternative anticoagulants (argatroban and lepirudin) have been Food and Drug Administration (FDA)-approved for HIT; one of these (lepirudin) has been withdrawn from production by the manufacturer as of 2012. Argatroban, a parenteral direct thrombin inhibitor (DTI), has been the drug of fi rst choice for HIT at many institutions, and is now the only FDA-approved medication for the treatment of HIT in the United States. Formally approved indications for argatroban are for prophylaxis or treatment of thrombosis in patients with HIT (United States and Japan), for patients with or at risk for HIT undergoing percutaneous coronary intervention (PCI) (United States and Japan), for patients with HIT undergoing hemodialysis (Japan), and for adult patients with HIT who require parenteral antithrombotic therapy (Austria, Canada, Denmark, Finland, France, Germany, Iceland, Italy, Netherlands, Norway, Spain, and Sweden). This chapter reviews the pharmacology of argatroban, its effi cacy and safety in HIT, and practical aspects of dosing, monitoring, and use in special populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".