Obesity and Metabolic Syndrome Are Independent Risk Factors for Atrial Fibrillation After Coronary Artery Bypass Graft Surgery
Bibliographic record
Abstract
BACKGROUND: Postoperative atrial fibrillation (POAF) is a highly prevalent complication after cardiac surgery with substantial effects on outcomes. Previous studies have reported that obesity is a risk factor for POAF after cardiac surgery. However, it is unknown whether the metabolic syndrome (MS) also increases the risk of postoperative atrial fibrillation. METHODS AND RESULTS: We retrospectively analyzed the association between obesity and MS and the incidence of new-onset POAF in a total of 5085 patients who underwent isolated coronary artery bypass grafting surgery with no concomitant valvular surgery. Of these patients, 1468 (29%) were obese (body mass index > or = 30 kg/m2) and 2320 (46%) had a MS as defined by the NCEP-ATPIII. POAF occurred in 1374 (27%) of the patients. Obesity was associated (P<0.001) with increased incidence of POAF in the whole cohort as well as in patients > 50 years old but not in patients < or = 50 years old. In these patients, MS was the only metabolic factor to be significantly associated with higher incidence of POAF (12% versus 6%, P=0.01). In > 50-year-old patients, mild (30 < or = body mass index < 35 kg/m2) and moderate-severe (body mass index > or = 35 kg/m2) obesity were independently associated with a 1.4-fold (95% CI: 1.10 to 1.71; P=0.004) and 2.3-fold (95% CI: 1.71 to 3.13; P<0.0001) increase in the risk of POAF, respectively. In < or = 50-year-old patients, MS (relative risk [RR]: 2.36; 95% CI: 1.10 to 5.12; P=0.02) but not obesity was independently associated with POAF. CONCLUSIONS: This study demonstrates that obesity is a powerful risk factor for the occurrence of POAF after isolated coronary artery bypass grafting surgery in patients older than 50 years. However, in the younger population, this association is not observed and MS is the only metabolic risk factor to be independently associated with POAF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".