Subclinical postoperative atrial fibrillation: a randomized trial
Bibliographic record
Abstract
Background Postoperative atrial fibrillation (POAF) is the most common complication of cardiac surgery, requiring interventions and prolonging hospital stay. POAF is associated with increased mortality and a higher rate of systemic thrombo-embolism. The rates of recurrent AF, optimal follow-up and management remain unclear. We aimed to evaluate the incidence of recurrent atrial fibrillation (AF) events, during long term follow-up in patients with POAF following cardiac surgery. Methods Patients with POAF and a CHA 2 DS 2 -VASc score of ≥2 were randomized in a 2:1 ratio to either implantation of a loop recorder (ILR) or ECG monitoring using periodic Holters. Participants were followed prospectively for 2 years. The primary end point was the occurrence of AF longer than 5 min. Results The final cohort comprised of 22 patients, of whom 14 received an ILR. Over a median follow up of 25.7 (IQR of 24.7–44.4) months, 8 patients developed AF, representing a cumulative annualized risk of AF recurrence of 35.7%. There was no difference between ILR (6 participants, 40%) and ECG/Holter (2 participants, 25% p = 0.917). All 8 patients with AF recurrence were treated with oral anticoagulation. There were no cases of mortality, stroke or major bleeding. Two patients underwent ILR explantation due to pain at the implantation site. Conclusions The rate of recurrent AF in patients with POAF after cardiac surgery and a CHA 2 DS 2 -VASc score of ≥2 is approximately 1 in 3 when followed systematically. Further research is need to assess the role of ILRs in this population.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| 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".