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Rivaroxaban dosing in patients with atrial fibrillation: results from the RIVER registry – is dosing according to renal function appropriate?

2021· article· en· W3205593194 on OpenAlexaff
A. John Camm, Saverio Virdone, Keith A.A. Fox, Karen S. Pieper, Jan Beyer‐Westendorf, J.‐Y. Le Heuzey, Sylvia Haas, Gloria Kayani, Bernard J. Gersh, Alexander G.G. Turpie, A. K. Kakkar

Bibliographic record

VenueEuropean Heart Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRivaroxabanMedicineDosingRenal functionAtrial fibrillationStroke (engine)Hazard ratioInternal medicineThromboembolic strokeCreatinineCardiologyAnesthesiaWarfarinConfidence interval

Abstract

fetched live from OpenAlex

Abstract Introduction Rivaroxaban is recommended as an option for anticoagulation in patients with nonvalvular atrial fibrillation (AF) with one or more risk factors for stroke. The approved/recommended rivaroxaban dose for stroke prevention in patients with atrial fibrillation (AF) is solely based on renal function: 20 mg once daily (od) for patients with a creatinine clearance [CrCl] ≥50 ml/min and 15 mg od in patients with CrCl 15–49 mL/min). Purpose To assess the patterns of rivaroxaban prescription as per the creatinine clearances levels and to assess the impact of the rivaroxaban dosing on the rate of events at 2-year follow-up in patients with AF. Methods RIVaroxaban Evaluation in Real Life setting (RIVER) is a prospective international registry of patients with newly diagnosed non-valvular AF treated with rivaroxaban for the prevention of thromboembolic stroke and at least one investigator-determined risk factor for stroke. Adjusted hazard ratios (HRs) were obtained through Cox proportional-hazard model. Results Among 3402 patients with normal renal function (CrCl ≥50 mL/min), 82.1% were prescribed the recommended rivaroxaban dose of 20 mg (od) at baseline. Among 524 patients with moderate or severe renal impairment (CrCl 15–50 mL/min), 55.3% patients received rivaroxaban 15 mg (od), 39.9% received 20 mg (od) and 4.2% 10 mg (od). Non-recommended dosing was rare in patients younger than 70 (13.5%) but more frequent in older patients (28.8%). Non-recommended low dosing was more frequent in Asians (38.9%), compared to non-Asian patients (13.8%). Regarding clinical outcomes, adjusted hazards ratios (HR, presented with 95% confidence intervals) showed that the non-recommended low dosing (<20 mg od) was associated with higher risk of non-cardiovascular mortality (HR 2.09 (1.16–3.77)) in patients with normal renal function. The non-recommended high dosing (>15 mg od) was associated with lower risk of all-cause mortality (HR 0.63 (0.42–0.93)) and cardiovascular mortality (HR 0.32 (0.13–0.77)) and higher risk of major bleeding (HR 2.86 (1.49–5.50)) in patients with moderate to severe renal impairment (figure 1 and 2). Conclusion In patients with normal renal function, non-recommended low dose rivaroxaban was associated with increased cardiovascular mortality without reducing the risk of major bleeding compared to recommended dosing. In patients with CrCl <50 ml/min, non-recommended high dose rivaroxaban was associated with reduced cardiovascular mortality but at the cost of increased major bleeding. These observational data largely support the reduction of rivaroxaban dosing according to renal function but educational strategies are needed to ensure that rivaroxaban is used appropriately. Funding Acknowledgement Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): This work was supported by an unrestricted research grant from Bayer AG, Berlin, Germany, to TRI, London, UK, which sponsors the RIVER registry. This work is supported by KANTOR CHARITABLE FOUNDATION for the Kantor-Kakkar Global Centre for Thrombosis Science.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.056
GPT teacher head0.294
Teacher spread0.238 · 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".

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Citations1
Published2021
Admission routes1
Has abstractyes

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