Assessment of Recurrence Risk After Unprovoked Venous Thromboembolism
Bibliographic record
Abstract
Letters3 May 2011Assessment of Recurrence Risk After Unprovoked Venous ThromboembolismAlfonso Iorio, MD and James Douketis, MDAlfonso Iorio, MDFrom McMaster University, Hamilton, Ontario L8N 3Z5, Canada.Search for more papers by this author and James Douketis, MDFrom McMaster University, Hamilton, Ontario L8N 3Z5, Canada.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-154-9-201105030-00016 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail IN RESPONSE:We agree with Dr. Rodger and colleagues that teasing out the effects of age, sex, and hormonal therapy (such as oral contraceptives and estrogen replacement) in patients with VTE is important in estimating an individual patient's risk for disease recurrence and, thus, his or her need for long-term anticoagulation. They correctly state that VTE recurs more frequently in men than women (1, 2). However, age and use of hormonal therapy may confound assessment of the effect of a patient's sex on the risk for VTE recurrence. For example, women who receive oral contraceptives typically are younger than those ...References1. McRae S, Tran H, Schulman S, Ginsberg J, Kearon C. Effect of patient's sex on risk of recurrent venous thromboembolism: a meta-analysis. Lancet. 2006;368:371-8. [PMID: 16876665] CrossrefMedlineGoogle Scholar2. Rodger MA, Kahn SR, Wells PS, Anderson DA, Chagnon I, Le Gal G, et al. Identifying unprovoked thromboembolism patients at low risk for recurrence who can discontinue anticoagulant therapy. CMAJ. 2008;179:417-26. [PMID: 18725614] CrossrefMedlineGoogle Scholar3. Clinical Decision Rule Validation Study to Predict Low Recurrent Risk in Patients with Unprovoked Venous Thromboembolism (REVERSEII). Accessed at clinicaltrials.gov/ct2/show/NCT00967304 on 15 February 2011. Google Scholar4. d-Dimer to Select Patients With a First Unprovoked Venous Thromboembolism Who Can Have Anticoagulants Stopped at 3 Months (DODS). Accessed at clinicaltrials.gov/ct2/show/NCT00720915 on 15 February 2011. Google Scholar5. d-Dimer and ULtrasonography in Combination Italian Study (DULCIS). Accessed at clinicaltrials.gov/ct2/show/NCT00954395 on 15 February 2011. Google Scholar Author, Article, and Disclosure InformationAffiliations: From McMaster University, Hamilton, Ontario L8N 3Z5, Canada.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M10-0798. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoPatient-Level Meta-analysis: Effect of Measurement Timing, Threshold, and Patient Age on Ability of d-Dimer Testing to Assess Recurrence Risk After Unprovoked Venous Thromboembolism James Douketis , Alberto Tosetto , Maura Marcucci , Trevor Baglin , Mary Cushman , Sabine Eichinger , Gualtiero Palareti , Daniela Poli , R. Campbell Tait , and Alfonso Iorio Assessment of Recurrence Risk After Unprovoked Venous Thromboembolism Marc A. Rodger , Timothy Ramsay , Gregoire Le Gal , and Marc Carrier Metrics 3 May 2011Volume 154, Issue 9Page: 644KeywordsBody mass indexConflicts of interestDisclosureEstrogen replacement therapyHormonal therapyObesityOral contraceptive therapyRegression analysisVenous thromboembolism ePublished: 3 May 2011 Issue Published: 3 May 2011 Copyright & PermissionsCopyright © 2011 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".