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Record W3106792472 · doi:10.1136/esmoopen-2020-000948

Prevention of venous thromboembolism in ambulatory patients with cancer

2020· review· en· W3106792472 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

VenueESMO Open · 2020
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsJewish General HospitalMcGill UniversityOttawa HospitalUniversity of Ottawa
FundersBayer
KeywordsMedicineApixabanAmbulatoryRivaroxabanCancerLow molecular weight heparinWarfarinAnticoagulantRegimenIntensive care medicineThrombosisComplicationVenous thromboembolismClinical trialVenous thrombosisInternal medicineAtrial fibrillation

Abstract

fetched live from OpenAlex

Patients with cancer are at high risk of venous thromboembolic events, and this risk can be further increased in patients with certain cancer types and by cancer treatments. Guidelines on the prevention of cancer-associated thrombosis (CAT) recommend thromboprophylaxis for hospitalised patients; however, this is not routinely recommended for ambulatory patients receiving chemotherapy and is limited to specified high-risk patients. Identification of the ambulatory patients at risk of CAT who would most benefit from anticoagulant therapy is therefore critical to reduce the incidence of this complication. For patients receiving thromboprophylaxis for CAT, treatment options include low molecular weight heparin, acetylsalicylic acid, warfarin or direct oral anticoagulants (apixaban or rivaroxaban), dependent on the cancer type and cancer treatment regimen. This review discusses emerging clinical trial data and their potential clinical impact.

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 score0.974
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 head0.052
GPT teacher head0.376
Teacher spread0.324 · 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