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Record W2027200715 · doi:10.2147/vhrm.s54714

Benefit–risk assessment of rivaroxaban versus enoxaparin for the prevention of venous thromboembolism after total hip or knee arthroplasty

2014· article· en· W2027200715 on OpenAlexaff
Bennett Levitan, Žhong Yuan, Alexander G.G. Turpie, Richard J. Friedman, Martin Homering, Jesse A. Berlin, Scott D. Berkowitz, Rachel Weinstein, Peter M. DiBattiste

Bibliographic record

VenueVascular Health and Risk Management · 2014
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcMaster UniversityHamilton Health Sciences
FundersBayer HealthCareJanssen Scientific Affairs
KeywordsMedicineRivaroxabanNumber needed to harmPulmonary embolismDeep veinNumber needed to treatAdverse effectPlaceboAnesthesiaSurgeryThrombosisRelative riskInternal medicineWarfarinConfidence intervalAtrial fibrillation

Abstract

fetched live from OpenAlex

PURPOSE: Venous thromboembolism is a common complication after major orthopedic surgery. When prescribing anticoagulant prophylaxis, clinicians weigh the benefits of thromboprophylaxis against bleeding risk and other adverse events. Previous benefit-risk analyses of the REgulation of Coagulation in ORthopaedic surgery to prevent Deep vein thrombosis and pulmonary embolism (RECORD) randomized clinical studies of rivaroxaban versus enoxaparin after total hip (THA) or knee (TKA) arthroplasty generally used pooled THA and TKA results, counted fatal bleeding as both an efficacy and a safety event, and included the active and placebo-controlled portions of RECORD2, which might confound benefit-risk assessments. We conducted a post hoc analysis without these constraints to assess benefit-risk for rivaroxaban versus enoxaparin in the RECORD studies. PATIENTS AND METHODS: Data from the safety population of the two THA and two TKA studies were pooled separately. The primary analysis compared the temporal course of event rates and rate differences between rivaroxaban and enoxaparin prophylaxis for symptomatic venous thromboembolism plus all-cause mortality (efficacy events) versus nonfatal major bleeding (safety events). Additionally, these rates were used to derive measures of net clinical benefit, number needed to treat (NNT), and number needed to harm (NNH) for these two end points. RESULTS: After THA or TKA, and compared with enoxaparin, rivaroxaban therapy resulted in more efficacy events prevented than safety events caused, with benefits exceeding harms early and throughout treatment and follow-up. Relative to enoxaparin, rivaroxaban treatment prevented six efficacy events per harm event caused for THA, with NNT =262/NNH =1,711. For TKA, rivaroxaban treatment prevented four to five efficacy events per harm event caused, with NNT =102/NNH =442. Sensitivity analysis that included surgical-site bleeding resulted in NNH =345 for THA and NNH =208 for TKA. CONCLUSION: In the RECORD studies, considering death, symptomatic venous thromboembolism, and major bleeding, rivaroxaban resulted in greater benefits than harms compared with enoxaparin. When incorporating surgical-site bleeding, rivaroxaban also results in greater benefit than harm for TKA and is balanced with enoxaparin for THA.

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)0.018
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.031
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.007
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.019
GPT teacher head0.308
Teacher spread0.289 · 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 designMeta-analysis
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

Citations34
Published2014
Admission routes1
Has abstractyes

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