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Impact of Atrial Fibrillation, Diabetes Mellitus, and Obesity on Outcomes With Aspirin Avoidance and Hemocompatibility With a Left Ventricular Assist Device: An Analysis From the ARIES-HM3 Trial

2025· article· en· W4416815208 on OpenAlexaff
Nir Uriel, Ivan Netuka, Ulrich P. Jorde, Francis D. Pagani, Jason N. Katz, Jean M. Connors, Peter Ivák, Daniel Zimpfer, Yuriy Pya, Jennifer Conway, Finn Gustafsson, Sriram Nathan, Anna Mara Scandroglio, Chris Hayward, David A. D’Alessandro, Morgan E. Collins, Nicholas Dirckx, Mandeep R. Mehra

Bibliographic record

VenueJournal of Cardiac Failure · 2025
Typearticle
Languageen
FieldEngineering
TopicMechanical Circulatory Support Devices
Canadian institutionsUniversity of Alberta HospitalAlberta Hospital Edmonton
FundersAbbott PharmaceuticalsAgency for Healthcare Research and QualityAbiomedCSL BehringNational Heart, Lung, and Blood InstituteAlnylam PharmaceuticalsAbbott LaboratoriesSanofiAstraZenecaPfizerBristol-Myers Squibb
KeywordsAspirinDiabetes mellitusObesityVentricular assist deviceClinical trialReduction (mathematics)

Abstract

fetched live from OpenAlex

BACKGROUND: The ARIES-HM3 trial demonstrated the safety and effectiveness of aspirin elimination from the antithrombotic regimen after HeartMate 3 (HM3) left ventricular assist device (LVAD) implantation. We explored the interaction of atrial fibrillation, diabetes mellitus, and obesity (AF/DM/Ob) with aspirin elimination on hemocompatibility-related adverse events at 1-year postimplant. METHODS: level suppression. RESULTS: levels. CONCLUSION: Among ARIES-HM3 trial patients with AF/DM/Ob, no comorbidity, alone or in combination, altered the safety or observed effect size on bleeding reduction with aspirin elimination in patients implanted with the HM3 LVAD.

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)0.004
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.007
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.244
Teacher spread0.237 · 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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractno

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