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Record W4412602731 · doi:10.1016/j.rpth.2025.102985

Radiotherapy—the not-so-insignificant contributor to cancer-associated venous thrombosis

2025· review· en· W4412602731 on OpenAlexaff
Gerard Gurumurthy, Jacob Miller, Marc Carrier, Alok A. Khorana, Jecko Thachil

Bibliographic record

VenueResearch and Practice in Thrombosis and Haemostasis · 2025
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersSanofiLEO Pharma Research FoundationImperial College LondonPfizer
KeywordsVenous thrombosisRadiation therapyMedicineCancerThrombosisVenous thromboembolismIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Venous thromboembolism is a well-established complication in patients with cancer and a leading cause of morbidity and mortality in these subjects. However, the role of radiotherapy in cancer-associated venous thromboembolism (CAT) remains less clearly defined. The incidence of CAT in this population varies widely, with several large-scale studies suggesting an association. Although management of CAT in this population follows standard guidelines, less is known about the appropriateness of thromboprophylaxis in patients with different types of cancer. Patients with cancer undergoing radiotherapy may also be at increased risk of bleeding, which may be further worsened by anticoagulation. A multidisciplinary approach integrating hematology and oncology expertise is essential in this setting. Further research is needed to establish standardized protocols and predictive models to identify those at risk of thrombosis and bleeding while on anticoagulation.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.248
GPT teacher head0.520
Teacher spread0.271 · 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 designNot applicable
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

Citations4
Published2025
Admission routes1
Has abstractyes

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