Abstract 13436: Sex-Specific Predictors of Postoperative Atrial Fibrillation and the Role of Cardiometabolic Diseases
Bibliographic record
Abstract
Introduction: Cardiometabolic diseases increase the risk of postoperative atrial fibrillation (POAF), which in turn is associated with higher long-term risk of major cardiovascular events (MACE). Little is known regarding the sex-specific impact of cardiometabolic diseases on POAF risk. We evaluated the sex-specific predictors of POAF after coronary artery bypass grafting (CABG), with a focus on preoperative cardiometabolic profile. Methods: In a prospective registry of patients undergoing isolated CABG (2006-2019), we compared predictors of POAF between sexes. We excluded patients with previous AF history, redo/urgent/off-pump CABG, perioperative mortality, and permanent pacemakers/defibrillators. Abdominal obesity was defined as a waist circumference (WC) >102 cm (men [M]) or >88 cm (women [W]). Results: We included 7,851 patients (19% women). Baseline characteristics are presented in Table 1. POAF occurred in 27% of women and 31% of men (p<0.01). Women were older and had a higher prevalence of comorbidities, abdominal obesity and a worse lipid profile. In a logistic regression model adjusting for the variables in Table 1, men had a higher risk of POAF (OR M = 1.4 [1.2-1.6], p<0.01). When stratifying by sex, significant predictors (p<0.05) of POAF for both sexes were age, WC (OR M = 1.04 [1.00-1.08]; OR W = 1.01 [1.00-1.03]), and triglycerides (TG) (OR M = 0.98 [0.97-0.99]; OR W = 0.97 [0.95-0.99]). Sex-specific predictors were creatinine for women and beta-blockers, extracorporeal circulation time, intensive care stay and hemoglobin for men. Conclusions: Women had less POAF but worse preoperative cardiometabolic profile compared to men. WC was a strong predictor of POAF for both sexes, while higher TG levels were protective. Since POAF is linked to future risk of MACE, the preoperative clinical assessment of WC should be encouraged and targeted for preventive strategies, especially in women. More studies are needed to investigate the role of TG in POAF.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".