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The association between sex and body size and stroke risk and survival in patients with atrial fibrillation - an analysis of 71,589 patients from the COMBINE-AF study

2025· article· en· W7127906527 on OpenAlexaff
Julia Aulin, Erika Frank, J Lindback, M C Bahit, E P Belley-Cote, E A Bohula, J W Eikelboom, R P Giugliano, C B Granger, E M Hylek, S M Al-Khatib, P A Merlini, D M Siegal, M Tannu, Lars Wallentin

Bibliographic record

VenueEuropean Heart Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversity of OttawaMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsAtrial fibrillationStroke (engine)WarfarinHeart failureDiabetes mellitusRandomized controlled trialEmbolismRisk factor

Abstract

fetched live from OpenAlex

Abstract Background In patients with atrial fibrillation (AF), the risk of stroke is higher and mortality is lower in females than males. Whether a smaller body size in female patients is associated with outcomes is uncertain. Purpose We assessed the risk of stroke/systemic embolism (SE), major bleeding, cardiovascular (CV) death and all-cause death in female vs male patients with AF treated with warfarin or a DOAC, and sought to determine whether the risks are modified by demographics and clinical characteristics including weight and height. Methods We used pooled patient-level data from 4 large RCTs investigating DOACs vs warfarin (ARISTOTLE, ENGAGE AF-TIMI 48, RE-LY, ROCKET) from the COMBINE-AF cohort. Stepwise Cox-regression analyses were used to adjust for factors modifying the associations with outcomes. Four models were constructed as follows: Model 0: no adjustment; Model 1: age + trial + randomized treatment; Model 2A: model 1 + prior stroke/TIA + congestive heart failure + diabetes + hypertension + vascular disease; Model 2B: model 1 + creatinine + weight + height; and Model 3: model 2 (A+B) + region + type of AF + VKA experience. Results Data were available for 71,589 patients (26,659 females). Median age was 73 [IQR 67-78] and 71 [63-77] years, median height 160.0 [155.0 – 165.0] and 174.0 [168.0 – 180.0] cm, median weight 73.0 [63.0 – 85.0] and 85.3 [75.0 – 98.2] kg in females and males, respectively. During 2.3 [1.50, 2.67] years median follow-up, there were 2,494 stroke/SE, 1,960 ischaemic stroke/SE, 648 intracranial bleeding, 1,584 gastrointestinal bleeding, 3,660 CV death and 5,818 all-cause death. Yearly incidence rates of stroke/SE 1.99 [1.88, 2.12] vs 1.59 [1.51, 1.68] and ischaemic stroke/SE 1.60 [1.49, 1.71] vs 1.23 [1.16, 1.31] were higher in females than males. In Cox models, female sex was not independently associated with stroke after adjustment for height and weight (Figure 1). Rates of gastrointestinal bleeding 1.16 [1.06, 1.26] vs 1.32 [1.24, 1.40], CV death 2.23 [2.10, 2.35] vs 2.69 [2.59, 2.80] and all-cause death 3.56 [3.40, 3.72] vs 4.27 [4.13, 4.40] were lower in females vs males. Female sex was independently associated with less bleeding and lower mortality, and with a greater magnitude after adjustment for height and weight (Figure 1). Figure 2 displays the inverse associations between height and weight across the range for stroke and up to 80 kg body weight and 170 cm length for CV mortality. Conclusion In patients with AF treated with an OAC, there is a higher rate of stroke in females than males but no independent association between female sex and the risk of stroke/SE. There is a continuous independent inverse association between a smaller body size and a higher risk of stroke/SE, and also an independent inverse association between a smaller body size and higher CV death up to a body weight of 80 kg and height of 170 cm.Figure 1.Cox regression analyses Figure 2.Predicted event rates

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)0.004
metaresearch head score (Gemma)0.005
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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.005
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.022
GPT teacher head0.296
Teacher spread0.273 · 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
Published2025
Admission routes1
Has abstractyes

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