Recurrence of Postoperative Atrial Fibrillation After Cardiac Surgery: Insights from a Tertiary Follow-Up Clinic
Bibliographic record
Abstract
Background: New-onset postoperative atrial fibrillation (POAF) complicates 30% of cardiac surgeries. Although POAF is often transient, structured follow-up care of patients with POAF may identify those with paroxysmal or persistent atrial fibrillation (AF) who will benefit from evidence-based therapies. Methods: This retrospective study includes patients seen in a clinic dedicated to patients with POAF after cardiac surgery between 2020 and 2024. Per the clinic's operating procedure, patients wore a 14-day continuous ambulatory electrocardiogram (ECG) monitor fpr 2 months after surgery and were assessed thereafter in clinic. The primary outcome was recurrent AF lasting ≥ 30 seconds, captured by 14-day continuous ambulatory ECG or during clinical care. Results: -VASc) score of 2 (interquartile range [IQR] 1-3); 529 patients (60.0%) underwent isolated coronary artery bypass grafting. At discharge, 798 patients (90.6%) were prescribed amiodarone, and 435 (49.4%) were prescribed oral anticoagulation. The mean time between discharge and 14-day continuous ambulatory ECG monitor was 72 days (IQR 61-84). AF recurrence was detected in 94 patients (10.7%); 30 patients (36.1%) were not receiving oral anticoagulation at the time of recurrence. Among patients with recurrence detected by 14-day continuous ambulatory ECG, the median duration was 10 hours (IQR 2-253). Left atrial volume index was the only independent predictor of AF recurrence. Following the clinic visit, oral anticoagulation was continued in 122 patients (28.2%). Conclusions: Among patients with POAF following cardiac surgery, 1 in 10 have AF recurrence, as determined by a structured 14-day continuous ambulatory ECG monitor utilized 2-3 months postoperatively.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".