MétaCan
Menu
← Back to cohort

P3968Does dual-antiplatelet therapy decrease the risk of stroke following coronary artery bypass grafting?

2017· article· en· W2762777438 on OpenAlexaff
Julian P. T. Higgins, Jamil Bashir, James G. Abel, Karin H. Humphries, Patrick Daniele, M.K. Lee

Bibliographic record

VenueEuropean Heart Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsSt. Paul's HospitalSt Mary's Hospital Centre
Fundersnot available
KeywordsMedicineBypass graftingCardiologyArteryStroke (engine)Internal medicine

Abstract

fetched live from OpenAlex

Introduction: Stroke can be a devastating complication following coronary artery bypass grafting (CABG). Recent trials suggest increased rates of stroke in CABG vs percutaneous coronary intervention (PCI), even beyond the first 30 days. There are suggestions that differences in medical management between these 2 groups, including increased use of dual antiplatelet therapy (DAPT) post-PCI, may contribute to differences in mid-term rates of stroke. Purpose: To determine whether the use of DAPT post-operatively, compared to ASA alone, decreases the risk of stroke after discharge, following isolated CABG. Methods: Prospectively maintained provincial registry accessed to identify all residents, ≥20 years of age, undergoing primary isolated CABG between April 2007-December 2012, and discharged home on either (1)ASA or (2)ASA & clopidogrel (DAPT). Baseline characteristics compared using Chi-square and Wilcoxon rank sum tests. Fisher's exact test used to compare 30-day mortality and combined 30-day stroke/death. Cumulative mortality and cumulative stroke/death curves calculated up to 5 years. Five year cumulative event rates estimated using Kaplan-Meier method. Cox proportional hazards model used to determine unadjusted and adjusted hazard ratios for DAPT use on 5-year stroke/death outcome.

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)0.000
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.001

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 head0.028
GPT teacher head0.283
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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Heart Journal→Same topicAntiplatelet Therapy and Cardiovascular Diseases→French-language works237,207→