MétaCan
Menu
← Back to cohort
Record W4395012741 · doi:10.1101/2024.04.20.24306039

Sex-specific association of cardiovascular drug doses with adverse outcomes in atrial fibrillation

2024· preprint· en· W4395012741 on OpenAlexafffund
Jeanne Moor, Michael Kühne, Giorgio Moschovitis, Richard Kobza, Seraina Netzer, Angelo Auricchio, Jürg H. Beer, Leo H. Bonati, Tobias Reichlin, David Conen, Stefan Osswald, Nicolas Rodondi, Carole Clair, Christine Baumgartner, Carole E. Aubert

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
FundersHamilton Health SciencesSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungFoundation for Cardiovascular ResearchSchweizerische Akademie der Medizinischen WissenschaftenSanofiUniversität BaselBristol-Myers SquibbDaiichi-SankyoMcMaster UniversityPfizerNational Science Foundation
KeywordsMaceMedicineAtrial fibrillationHeart failureInternal medicineHazard ratioQuartileCardiologyMyocardial infarctionEjection fractionProportional hazards modelPercutaneous coronary interventionConfidence interval

Abstract

fetched live from OpenAlex

Abstract Objectives Women with heart failure (HF) with reduced ejection fraction receiving submaximal doses of beta-blockers and renin-angiotensin system (RAS) inhibitors have a lower risk of mortality or hospitalizations for heart failure. However, optimal doses of beta-blockers or RAS inhibitors in women with atrial fibrillation (AF) with and without HF are unclear. We investigated sex-specific associations of beta-blocker and RAS inhibitor doses with cardiovascular outcomes in patients with AF with and without HF. Methods We used data from the prospective BEAT-AF and Swiss-AF cohorts on patients with AF. The outcome was major adverse cardiovascular events (MACE), including death, myocardial infarction, stroke, systemic embolization, and HF-related hospitalization. Predictors of interest were spline (primary analysis) or quartiles (secondary analysis) of beta-blocker or RAS inhibitor dose in percent of the maximum dose (reference), in interaction with sex. Cox models were adjusted for demographics, comorbidities and co-medication. Results Among 3,961 patients (28% women), MACE occurred in 1,113 (28%) patients over 5-year median follow-up. Distributions of RAS inhibitor and beta-blocker doses were similar in women and men. Cox models revealed no association between beta-blocker dose or RAS inhibitor dose and MACE. In a subgroup of patients with AF and HF, the lowest hazard of MACE was observed in women prescribed 100% of RAS inhibitor dose. However, there was no association between RAS dose quartiles and MACE. Conclusions In these two cohorts of patients with AF, doses of beta-blockers and RAS inhibitors did not differ by sex and were overall not associated with MACE. What is already known on the subject Sex-specific analyses of beta-blocker and renin angiotensin system (RAS) inhibitor doses in patients with heart failure with reduced ejection fraction have revealed a lower hazard of death or heart failure-related hospitalisation in women receiving low doses compared to maximum doses. The pathophysiology and pharmacotherapy of atrial fibrillation show sex differences, but the potential sex-specific associations of different drug doses with cardiovascular outcomes are unknown in this population. What this study adds This study identifies no associations between beta-blocker doses and major adverse cardiovascular events in patients with atrial fibrillation. How this study might affect research, practice or policy The findings of the present study reassure that the recommended maximum doses of beta-blockers and RAS inhibitors appeared safe among patients of both sexes with atrial fibrillation.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.289
Teacher spread0.256 · 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
Published2024
Admission routes2
Has abstractyes

Explore more

Same venuemedRxiv→Same topicAtrial Fibrillation Management and Outcomes→French-language works237,207→