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Record W2296429742 · doi:10.1182/blood.v124.21.343.343

Bleeding in Patients with Atrial Fibrillation Treated with Non Vitamin K Antagonist Oral Anticoagulants: A Population-Based Study

2014· article· en· W2296429742 on OpenAlexaff
Martin Ellis, Tsipora Neumann, Jeffrey S. Ginsberg, John W. Eikelboom, Haim Bitterman, Ariel Hammerman, Erez Battat, Sari Greenberg, Jack Hirsh

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcMaster UniversityThrombosis and Atherosclerosis Research Institute
Fundersnot available
KeywordsRivaroxabanDabigatranMedicineVitamin K antagonistAtrial fibrillationApixabanPopulationStroke (engine)WarfarinInternal medicineEdoxaban

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION Recent large randomized controlled trials (RCTs) have shown non-vitamin K antagonist oral anticoagulants (NOACs) are at least as effective as vitamin K antagonists (VKAs) for prevention of stroke or systemic embolism in patients with non-valvular atrial fibrillation (AF) and are associated with similar or lower rates of bleeding. The results for bleeding seen in Phase 3 trials might not be applicable to real world practice. We performed a large population-based study to determine the incidence of bleeding in patients with AF beginning treatment with dabigatran, rivaroxaban or a VKA. METHODS From the computerized database of the 4.5 million member Israeli Clalit Health Services health care provider, consecutive patients initiating a VKA or NOAC for AF between January 1, 2011 and December 31, 2013 were studied. For prevention of embolism in AF, dabigatran had regulatory approval for 36 months and rivaroxaban for 24 months. Bleeding patients who required hospitalization were identified and key clinical and laboratory data were recorded. Because patients received different anticoagulants for different durations, time-to-event analyses were performed and bleeding incidences were calculated and reported as rates per 100 patient-years of treatment. Bleeding sites and all-cause mortality within 30 days were recorded and case fatality rates were calculated as the proportions of bleeding patients who died within 30 days. RESULTS (Table1) 18249 patients initiated anticoagulants for AF: 9564 received VKA, 4170 received dabigatran 110 mg bid , 1806 received dabigatran 150 mg bid and 2709 received rivaroxaban. The bleeding rates per 100 patient-years were 3.9 in VKA-treated patients, 2.8 in dabigatran 150 mg patients, 4.6 in dabigatran 110 mg patients and 4.3 in rivaroxaban patients. The intracranial hemorrhage (ICH) rates per 100 patient-years were 0.70 in VKA-treated patients, 0.37 in dabigatran 150 mg patients, 0.49 in dabigatran 110 mg patients and 0.27 in rivaroxaban patients. The gastrointestinal (GI) hemorrhage rates per 100 patient-years were 1.88 in VKA-treated patients, 1.85 in dabigatran 150 mg patients, 3.36 in dabigatran 110 mg patients and 2.39 in rivaroxaban patients. The case fatality rate for any bleed was 21%; for ICH 28.8%, and for GI bleeds it was 11.1%. Multivariate analysis revealed that increased age and increased serum creatinine were risk factors for bleeding in NOAC-treated patients. CONCLUSIONS The results of our population-based non-randomized study of AF patients are consistent with the RCTs in showing similar rates of overall bleeding, an increase in GI bleeding associated with dabigatran and a reduction in ICH seen with both dabigatran and rivaroxaban. Table 1: Clinical profile of patient cohort VKA Dabigatran 150 mg Dabigatran 110 mg Rivaroxaban Overall Number of patients 9564 1806 4170 2709 18249 Age in years) Median (Range) 79 (27-99) 78 (52-89) 82 (55-95) 82 (58-91) 80 (27-99) Women % 43.8 45.1 47 38.6 43.7 Serum creatinine mg/dL Median (Range) 1.2 (0.3-11.6) 1.0 (0.5-4.4) 1.2 (0.4-4.1) 1.3 (0.5-3.5) 1.2 (0.3-11.6) CHADS2 score Median (Range) 3 (0-6) 3 (1-6) 4 (1-6) 4 (2-6) 3 (0-6) Anti aggregant use (%) 52 50 35 55 48 Bleeds per 100 patient years (N) 3.9 (372) 2.8 (50) 4.6 (191) 4.3 (116) (729) Fatalities within 1 month of hemorrhage N 44 8 15 3 70 Intracranial hemorrhage N 67 4 16 3 90 Gastrointestinal hemorrhage N 178 20 108 26 332 Disclosures Ellis: Boehringer Ingelheim: Honoraria. Eikelboom:Bayer: Honoraria, Research Funding; Bristol Meyers Squibb: Honoraria, Research Funding; Boehringer Ingelheim: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Daiichi Sankyo: Honoraria, Research Funding.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.019
GPT teacher head0.275
Teacher spread0.255 · 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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Citations2
Published2014
Admission routes1
Has abstractyes

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