New Standards in Antithrombotic Therapy: Concepts, Clinical Evidence, and Applications
Bibliographic record
Abstract
Venous thromboembolism (VTE) is a significant medical disorder. It can present as either silent or symptomatic deep venous thrombosis (DVT) or pulmonary embolism (PE). Approximately 200,000 new VTE events occur each year in the United States, and the incidence is expected to increase with the ``graying'' of America. Unfortunately, the initial presentation may be sudden death from a PE. Even among patients whose PE is heralded by symptoms, approximately 30% die within 30 days of the acute event. In addition to death, VTE events are associated with significant morbidity and health care costs. Therefore, it is important to reduce the incidence of VTE events, thereby improving survival and decreasing the incidence of both complications and recurrence. During the last 15 years, there has been an exponential growth in the field of antithrombotic therapy. Many of the new agents that have been developed, promising improved risk-benefit profiles, have been evaluated in well-designed, randomized clinical trials. With the large body of evidence on the safety and efficacy of the newer anticoagulants that has now accumulated, clinicians treating patients who present with VTE events or who are at risk for them should understand the concepts underlying antithrombotic therapy and to review the evidence pertaining to the use of current and new agents. With this foundation, they will be able to consider clinical applications for the novel medications. The material in this supplement is the result of a collaborative effort by clinical investigators with extensive experience in the field of venous thromboembolic disease. The information was originally presented in a symposium conducted in conjunction with the 2001 meeting of the American Society of Hematology. 1 The intent of the faculty was to educate the participants on the pathophysiology, medical significance, and economic importance of VTE events. The presentations highlighted the advantages and disadvantages of the current generation of antithrombotic interventions and addressed the need for improved VTE therapy, particularly in high-risk populations. These experts also explained the role of different strategies in the treatment of symptomatic VTE events as indicated by evidence from clinical trials. Despite noteworthy advances in VTE treatment, a number of issues still require resolution. The articles in this supplement represent the best of current thinking on this important clinical problem.[ * ]
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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 | 0.090 | 0.212 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".