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New aspects on treatment modalities for thromboembolic episodes

2010· review· en· W2167968560 on OpenAlexaff
Sam Schulman

Bibliographic record

VenueJournal of Internal Medicine · 2010
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineIntensive care medicineVitamin K antagonistThrombolysisDiseaseVenous thromboembolismThrombosisSurgeryInternal medicineWarfarinMyocardial infarction

Abstract

fetched live from OpenAlex

Venous thromboembolism (VTE) has been treated with a glycosaminoglycan, followed by a vitamin K antagonist during the past 60 years. During the past two decades the glycosaminoglycans have undergone refinement, allowing for simplification of care for these patients, but parenteral administration is still required. Therefore, the current completion of phase III trials with selective, predictable and orally available anticoagulants with rapid onset brings promise for a change in paradigm in the treatment of VTE in the next few years. Whereas these efforts will lead to further simplification of the therapy there are also trials conducted to advance the treatment by rapid resolution of the thromboembolism in order to improve long-term outcome. Catheter-directed thrombolysis, perhaps also with thrombus fragmentation and stent insertion, if demonstrated to be successful for the reduction of the postthrombotic syndrome, will only be an alternative for a minority of patients due to the complexity, risks and cost of therapy. This treatment increases the complexity at the same time as new drug regimens offer simplicity. This review focuses on the novel therapies for VTE although the new anticoagulants will also play a major role in the management of arterial disease, which will be briefly presented.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.003

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 head0.072
GPT teacher head0.393
Teacher spread0.321 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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