NOACs for treatment of venous thromboembolism in clinical practice
Bibliographic record
Abstract
Randomised controlled trials have provided important information on the efficacy and safety of the non-vitamin K antagonist oral anticoagulants (NOACs) for treatment of venous thromboembolism (VTE), leading to registration and increasing use in clinical practice. Many questions remain to be answered, and observational studies are often more suitable for answering "real-world" questions than randomised controlled trials. Patient satisfaction, quality of life, and adherence and persistence in clinical practice with the drug regimen can only be assessed with an open-label design. Evaluation of risk for long-term sequelae of the disease requires much longer follow-up than is possible in registration trials. Treatment patterns and utilisation of health care resources can be assessed from observations in the clinical practice setting. We will review published as well as currently active observational studies with NOACs in VTE, with or without a comparator anticoagulant. These studies are based on cohorts of different sizes, registries, or administrative health care databases. We will also discuss some limitations in analysis and interpretation of observational studies.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".