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Record W2912297541 · doi:10.1161/str.50.suppl_1.wmp85

Abstract WMP85: Clinical Effectiveness of Direct Oral Anticoagulants (DOACs) vs. Warfarin in Older Ischemic Stroke Patients With Atrial Fibrillation: Findings From Patient-Centered Research Into Outcomes Stroke Patients Prefer and Effectiveness Research (PROSPER) Study

2019· article· en· W2912297541 on OpenAlexaff
Ying Xian, Haolin Xu, Emily C. O’Brien, Shreyansh Shah, Laine Thomas, Michael Pencina, Gregg C. Fonarow, DaiWai M. Olson, Lee H. Schwamm, Deepak L. Bhatt, Eric E. Smith, Deidre Hannah, Brianna Lindholm, Lesley Maisch, Barbara L. Lytle, Eric D. Peterson, Adrian F. Hernandez

Bibliographic record

VenueStroke · 2019
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineAtrial fibrillationRivaroxabanWarfarinDabigatranApixabanMaceStroke (engine)Internal medicineEdoxabanHazard ratioPropensity score matchingCardiologyEmergency medicineConfidence intervalMyocardial infarctionPercutaneous coronary intervention

Abstract

fetched live from OpenAlex

Introduction: Direct oral anticoagulants (DOACs) are increasingly used as alternatives to warfarin for secondary prevention in ischemic stroke patients with atrial fibrillation. Despite demonstrated efficacy in clinical trials, there are few real-world experiences of DOACs vs. warfarin in community practice. Methods: We analyzed ischemic stroke survivors with atrial fibrillation discharged from the Get With The Guidelines Stroke hospitals between 2011-2014 and linked to Medicare claims for longitudinal outcomes through 2015. A propensity score overlap weighting method was used to compare DOACs vs. warfarin. The primary outcomes were major adverse cardiovascular events (MACE) and home time, a patient-centered outcome reflecting desire of “being alive at home, without recurrent stroke, or being hospitalized for complications.” Results: Among 11,662 stroke survivors (median age 80), 4,041 (34.7%) were discharged on DOACs (dabigatran, rivaroxaban, or apixaban) and 7,621 on warfarin. Except for NIHSS (median 4 [IQR 1-9] vs. 5 [2-11]), baseline demographics, medical history, and clinical characteristics were similar between two cohorts. Compared with warfarin, patients discharged on DOACs were less likely to experience MACE (33.95% vs. 40.36% per year, adjusted hazard ratio 0.89, 99% CI 0.83-0.96) and had more days at home (mean 287 vs. 263 days during the first year post discharge, adjusted difference 15.6 days, 99% CI 9.0-22.1) ( Table ). Additionally, there were fewer deaths, all-cause readmissions, cardiovascular readmissions, hemorrhagic strokes, and bleeding hospitalizations in DOAC-treated patients, although no significant differences in fatal bleeding, ischemic stroke readmission, systemic embolism, pneumonia, or sepsis (two negative outcome controls) between the two cohorts. Conclusions: In ischemic stroke survivors with atrial fibrillation, DOACs were associated with improved long-term clinical outcomes compared with warfarin.

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)0.026
metaresearch head score (Gemma)0.044
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 score0.026
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.009
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.050
GPT teacher head0.383
Teacher spread0.333 · 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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Citations0
Published2019
Admission routes1
Has abstractyes

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