Bibliographic record
Abstract
Argatroban is a small molecule direct thrombin inhibitor. The main attributes of this synthetic drug are its rapid onset of anti-thrombin action, rapid reversibility of its anticoagulant effect, potent inhibition of clot-bound thrombin, absence of antibody formation and no need for initial dosage adjustment in patients with renal impairment. It is eliminated by hepatic metabolism. These properties make argatroban a predictable anticoagulant with intravenous use in a routine clinical setting. Argatroban is approved in the US and Canada for both prophylaxis and treatment of thrombosis in patients with heparin-induced thrombocytopenia (HIT); and it is approved in Japan and Korea for treatment of various thrombotic disorders. Argatroban has been shown in limited trials to provide reliable anticoagulation during percutaneous coronary interventions on HIT and non-HIT patients. Preliminary reports document the feasibility of using argatroban for anticoagulation during peripheral vascular interventions, hemodialysis and as adjunct to thrombolysis for treatment of myocardial infarction. Current recommendations for argatroban monitoring are to use the activated partial thromboplastin time for low doses and the activated clotting time for high doses. The ease of monitoring argatroban, its 'turn-on/turn-off' characteristic and its consistent safety profile provide the rationale to continue studies of argatroban as an anticoagulant in clinical settings.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".