Antithrombotic Therapy for VTE Disease
Bibliographic record
Abstract
The American College of Chest Physicians (CHEST) Antithrombotic Therapy for Venous Thromboembolism Disease evidence-based guidelines are now updated in a more frequent, focused manner. Guidance statements from the most recent full guidelines and two subsequent updates have not been gathered into a single source. An international panel of experts with experience in prior antithrombotic therapy guideline development reviewed the 2012 CHEST antithrombotic therapy guidelines and its two subsequent updates. All guideline statements and their associated patient, intervention, comparator, and outcome questions were assembled. A modified Delphi process was used to select statements considered relevant to current clinical care. The panel further endorsed minor phrasing changes to match the standard language for guidance statements using the modified Grading of Recommendations, Assessment, Development, and Evaluations (ie, GRADE) format endorsed by the CHEST Guidelines Oversight Committee. The panel appended comments after statements deemed as relevant, including suggesting that statements be updated in future guidelines because of interval evidence. We include 58 guidance statements from prior versions of the antithrombotic therapy guidelines, with updated phrasing as needed to adhere to contemporary nomenclature. Statements were classified as strong or weak recommendations based on high-certainty, moderate-certainty, and low-certainty evidence using GRADE methodology. The panel suggested that five statements are no longer relevant to current practice. As CHEST continues to update guidance statements relevant to antithrombotic therapy for VTE disease, this article serves as a unified collection of currenrtly relevant statements from the preceding three guidelines. Suggestions have been made to update specific statements in future publications.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".