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Record W2532182114 · doi:10.1055/s-0036-1592305

Update on the Treatment of Venous Thromboembolism

2016· review· en· W2532182114 on OpenAlexaff
Sam Schulman

Bibliographic record

VenueSeminars in Thrombosis and Hemostasis · 2016
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcMaster UniversityThrombosis and Atherosclerosis Research Institute
Fundersnot available
KeywordsMedicinePulmonary embolismVenous thromboembolismVitamin K antagonistVitamin kThrombosisDeep veinMajor bleedingPlaceboVenous thrombosisIntensive care medicineWarfarinSurgeryInternal medicineAtrial fibrillationAlternative medicine

Abstract

fetched live from OpenAlex

During the past 7 years, results from phase III trials comparing nonvitamin antagonist K oral anticoagulants (NOACs) with vitamin K antagonists (VKAs) or with placebo, including 34,900 patients, have been published. Recent guidelines have been updated and now suggest treatment with NOACs rather than with VKA. Other updates in the guidelines concern the initial thrombolytic treatment for selected patients with deep vein thrombosis or pulmonary embolism as well as the possibility of withholding anticoagulation for minimal venous thromboembolism. The optimal duration of anticoagulation after an unprovoked event is still debatable, depending on values and preferences assigned to recurrent thromboembolism versus bleeding complications. The choice is essentially between a short duration of 3 or perhaps 6 months for extensive thromboembolism and indefinite duration. Several clinical prediction rules have been developed to aid in this choice but they all address only the risk of recurrent thrombosis without weighing in the risk of bleeding. This review provides an update on recent systematic reviews, meta-analyses, and guidelines on the treatment of venous thromboembolism.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.002

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.

Opus teacher head0.078
GPT teacher head0.367
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations12
Published2016
Admission routes1
Has abstractyes

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