Stepwise Anticoagulation with Warfarin for Prevention of Intravenous Catheter Thrombosis
Bibliographic record
Abstract
Warfarin is the most commonly used anticoagulant for prevention and therapy of thrombosis. Warfarin is a vitamin K antagonist and inhibits synthesis of clotting factors II, VII, IX, and X, and anticoagulant proteins C and S. Whereas there is extensive information about the efficacy of warfarin and target International Normalized Ratio (INR) for patients with artificial heart valves, atrial fibrillation, pulmonary emboli, deep venous thrombosis, and lupus anticoagulant, there is little in the literature on the role of warfarin in maintaining the patency of hemodialysis catheters. Much more is reported about the value of minidose warfarin in maintaining the patency of infusion catheters. Many centers have tried low-dose warfarin (1 mg per day), and found this not to be effective in preventing catheter thrombosis in many patients. Although most support the use of warfarin following catheterproblems, individual units have their own guidelines, with doses ranging from 2 mg per day (normal INR) to formal systemic anticoagulation with INR from 1.5 to 3.0. Stepwise anticoagulation with warfarin is emerging as useful in preventing catheter-associated thrombosis. With this method, patients are placed on low-dose warfarin after the first clotting episode. With each subsequent episode, the dose is increased, raising INR by 0.5 until clotting episodes do not recur. Warfarin doses similar to those in patients with artificial heart valves have been used in selected patients (target INR 3.0 - 4.0) to prevent clotting.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
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".