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Record W2033037810 · doi:10.1159/000217481

Treatment of Thrombotic Disorders in Cancer Patients

2009· review· en· W2033037810 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

VenueHaemostasis · 2009
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsOttawa Regional Cancer FoundationCancer Care Ontario
Fundersnot available
KeywordsMedicineHeparinThrombosisCancerDeep veinMalignancyLow molecular weight heparinVenous thrombosisAnticoagulantSurgeryInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

Cancer patients are in a hypercoagulable state. The pathogenesis of thrombosis in malignancy is multifactorial with mechanisms including release of procoagulants by tumour cells, comorbid predisposing factors (bed rest, infection, surgery, etc.) and anti-cancer drugs. Cancer patients with established venous thromboembolism are more likely to develop recurrent venous thromboembolism during treatment with oral anticoagulants. This paper reviews the use of heparin for the treatment of thrombotic disorders in cancer patients. Treatment of acute venous thrombosis comprises initial heparin administration, which for a cancer patient should last for at least 5 days, followed by administration of oral anticoagulants. Low-molecular-weight heparins (LMWHs) have been shown to be as safe and effective as standard heparin for the treatment of acute deep vein thrombosis. Recent meta-analyses have revealed lower mortality rates with LMWH than with standard heparin, indicating that LMWH may exert an inhibitory effect on tumour growth that is not observed with standard heparin.

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 score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
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 head0.064
GPT teacher head0.380
Teacher spread0.316 · 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