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Thrombosis in Cancer: An Update on Prevention, Treatment, and Survival Benefits of Anticoagulants

2010· review· en· W2101600191 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHematology · 2010
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsVancouver General HospitalUniversity of British ColumbiaVancouver Coastal Health
Fundersnot available
KeywordsMedicineAntithromboticIntensive care medicineThrombosisMalignancyAnticoagulantCancerLow molecular weight heparinHeparinOncologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Thromboembolism is a common, complex, and costly complication in patients with cancer. Management has changed significantly in the past decade, but remains firmly dependent on the use of anticoagulants. Low-molecular-weight heparin is the preferred anticoagulant for prevention and treatment, although its limitations open opportunities for newer oral antithrombotic agents to further simplify therapy. Multiple clinical questions remain, and research is focusing on identifying high-risk patients who might benefit from primary thromboprophylaxis, treatment options for those with established or recurrent thrombosis, and the potential antineoplastic effects of anticoagulants. Risk-assessment models, targeted prophylaxis, anticoagulant dose escalation for treatment, and ongoing research studying the interaction of coagulation activation in malignancy may offer improved outcomes for oncology patients.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.964
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.122
GPT teacher head0.423
Teacher spread0.301 · 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