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Patients with Cancer Who Develop a First Venous Thromboembolic Event After Surgery Are at High Risk of Venous Thromboembolism Recurrence During the Anticoagulation Period

2010· article· en· W2979766680 on OpenAlexaffabout
Martha Louzada, Alejandro Lazo‐Langner, Marc Carrier, Vi Dao, Jerry Zhang, Marc Rodger, Michael J. Kovacs, Philip Wells

Bibliographic record

VenueBlood · 2010
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsVictoria HospitalOttawa HospitalUniversity of OttawaCancerCare ManitobaLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicinePulmonary embolismThrombosisCancerSurgeryVenous thrombosisVenous thromboembolismRetrospective cohort studyMalignancyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Abstract 4202 Background: It is unknown whether patients with cancer who develop VTE after a surgical procedure have the same risk of recurrent VTE as clinical patients cancer-associated thrombosis. VTE recurrence risk in non-cancer patients with VTE after surgery is approximately 1% in the 3 months following completion of anticoagulation. It is unknown whether surgical patients with cancer follow the low risk of recurrence as other provoked VTEs or whether they have the high recurrence risk typical of cancer patients. Methods: We performed a post-hoc analysis of a single centre retrospective cohort study conducted at the Thrombosis Unit of the Ottawa Hospital. The charts of patients with cancer and VTE followed from 2002 to 2004 and from 2007 to 2008 were reviewed. We sought to compare the risk of recurrent VTE between patients with cancer who developed a first VTE after major surgery with all other patients with cancer-associated thrombosis. We included patients > or = 18 years of age with active malignancy and objectively diagnosed index VTE [pulmonary embolism (PE), proximal deep venous thrombosis (DVT) of the legs or arms, PE + DVT; unusual site thrombosis]. After the first VTE, all patients received a minimum of 6 months of anticoagulation. In the surgery group, index VTE was considered associated with the intervention if it occurred within the first 3 months after the procedure. Results: 543 patients were included. 121 patients had VTE after surgery and 17 (13.1%) developed a recurrence during therapeutic anticoagulation. Of 422 clinical patients, 61 (14.7%) had a recurrent VTE (Table). The relative risk of recurrent VTE comparing patients who had and who did not have surgery was non-significant (RR= 0.97 (95%CI: 0.587 – 1.574; p= 1.000) suggesting that patients with cancer who undergo surgery have similar risk of developing a recurrent VTE during anticoagulation as patients with cancer-associated VTE who do not undergo surgery. VTE recurrence occurred predominantly within the first 6 months of anticoagulation [Surgery: 9 of 17 patients (52.9 %); no surgery: 45 of 61 (73.7%) patients (p=0.1377)] (Figure). There was no significant difference in VTE recurrence risk according to anticoagulant strategy, tumor site, histology, TNM stage, age or gender between surgery and no surgery groups. Conclusion: Patients with cancer who develop VTE after surgery have similar risk of developing a recurrent VTE during the anticoagulation period as clinical patients with cancer-associated VTE. Disclosures: Rodger: Pfizer: Research Funding; Leo Pharma: Research Funding; Sanofi Aventis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Canadian Institutes of Health Research: Research Funding; Heart and Stroke Foundation: Research Funding.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.218
Teacher spread0.212 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2010
Admission routes2
Has abstractyes

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