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Record W2089621382 · doi:10.1186/1477-9560-12-16

XALIA: rationale and design of a non-interventional study of rivaroxaban compared with standard therapy for initial and long-term anticoagulation in deep vein thrombosis

2014· article· en· W2089621382 on OpenAlexaffabout
Walter Ageno, LG Mantovani, Sylvia Haas, Reinhold Kreutz, Verena Haupt, Jonas Schneider, Alexander GG Turpie

Bibliographic record

VenueThrombosis Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsHamilton Health SciencesHamilton General Hospital
FundersBayer HealthCareJanssen Scientific Affairs
KeywordsMedicineRivaroxabanVitamin K antagonistPulmonary embolismDeep veinThrombosisLow molecular weight heparinWarfarinVenous thrombosisIntensive care medicineSurgeryInternal medicineAtrial fibrillation

Abstract

fetched live from OpenAlex

Venous thromboembolism (VTE), comprising deep vein thrombosis (DVT) and pulmonary embolism, poses a substantial clinical risk, and the incidence of these thrombotic-related diseases remains high. Anticoagulation aims to prevent thrombus extension and reduce the risk of recurrent events, particularly fatal pulmonary embolism. In EINSTEIN DVT, rivaroxaban was non-inferior to enoxaparin/vitamin K antagonists for the reduction of recurrent VTE, with a similar safety profile and a net clinical benefit. EINSTEIN EXT investigated patients receiving long-term treatment in whom there was no clear decision about continuing or stopping anticoagulation; rivaroxaban was superior to placebo in the reduction of recurrent VTE, showing an acceptable benefit-risk balance. Rivaroxaban has the potential to replace standard therapy, usually parenteral low molecular weight heparin overlapping with and followed by a vitamin K antagonist, for the treatment of acute symptomatic DVT and the secondary prevention of VTE. As the use of rivaroxaban for DVT treatment increases in clinical practice, a fundamental understanding of its clinical benefits in everyday patient care is essential. XALIA (XArelto for Long-term and Initial Anticoagulation in venous thromboembolism) is a multicentre, prospective, non-interventional, observational study investigating the effectiveness and safety of a single-drug approach with rivaroxaban compared with standard therapy in patients with DVT. The study cohort will include approximately 4800 patients (≥18 years old) with objectively confirmed acute DVT who will be treated for a period of ≥3 months. The primary outcomes will be the incidence of treatment-emergent adverse events (primarily major bleeding), symptomatic recurrent venous thromboembolic events and all-cause mortality. Secondary outcomes include: major cardiovascular events; patient-reported treatment satisfaction and adherence; healthcare resource utilization; reasons for drug switching or interruption of treatment; and adverse events. XALIA will follow an international cohort of patients in more than 20 European countries, and others including Israel and Canada. The first patient was enrolled in June 2012, with results expected in 2015. It is anticipated that XALIA will provide important information on the treatment of DVT in a heterogeneous, unselected patient population in a real-world setting and provide important supplementary information to that obtained from the EINSTEIN DVT phase III study.

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)0.087
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.087
Threshold uncertainty score0.460

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0870.057
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0020.002
Science and technology studies0.0020.004
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0090.004

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 head0.064
GPT teacher head0.352
Teacher spread0.288 · 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 designNon-randomized trial
Domainnot available
GenreProtocol

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

Citations27
Published2014
Admission routes2
Has abstractyes

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