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Record W2284452669 · doi:10.1302/0301-620x.94b11.28955

The effects of rivaroxaban on the complications of surgery after total hip or knee replacement

2012· article· en· W2284452669 on OpenAlexaff
Michael R. Lassen, Michael Gent, A. K. Kakkar, Bengt I. Eriksson, Martin Homering, Scott D. Berkowitz, Alexander G.G. Turpie

Bibliographic record

VenueJournal of Bone and Joint Surgery - British Volume · 2012
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRivaroxabanMedicineKnee replacementTotal hip replacementSurgeryHip replacementArthroplastyInternal medicineAtrial fibrillationWarfarin

Abstract

fetched live from OpenAlex

Post-operative complications after total hip or knee replacement can delay recovery, prolong hospitalisation, increase rates of re-admission and, in the most severe cases, lead to long-term disability or even death. In this analysis of pooled data from four large, randomised, phase III clinical trials that compared the oral, direct Factor Xa inhibitor rivaroxaban with subcutaneous enoxaparin for the prevention of venous thromboembolism after total hip or knee replacement (n = 12,729), the incidence of complications, including bleeding and adverse events related to surgery (such as wound infection, wound dehiscence and haemarthrosis) are reported. Interventions and procedures relating to surgery are also compared between the groups. Bleeding events, including excessive wound haematoma and surgical-site bleeding, occurred at similar rates in the rivaroxaban and enoxaparin groups. Over the total study duration, adverse surgical events occurred at a similar rate in the rivaroxaban group compared with the enoxaparin group after total knee replacement (2.26% vs. 2.69%, respectively) and total hip replacement (1.48% vs. 1.65%, respectively). Blood loss, wound drainage and transfusion requirements were also similar between the two groups. This analysis shows that the incidence of adverse surgical events with rivaroxaban was similar to enoxaparin.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.712
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.024
GPT teacher head0.241
Teacher spread0.217 · 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 teacher head, 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

Citations46
Published2012
Admission routes1
Has abstractyes

Explore more

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