Society of Cardiovascular Anesthesiologists/European Association of Cardiothoracic Anaesthetists Practice Advisory for the Management of Perioperative Atrial Fibrillation in Patients Undergoing Cardiac Surgery
Bibliographic record
Abstract
Postoperative atrial fibrillation (poAF) is the most common adverse event after cardiac surgery and is associated with increased morbidity, mortality, and hospital and intensive care unit length of stay. Despite progressive improvements in overall cardiac surgical operative mortality and postoperative morbidity, the incidence of poAF has remained unchanged at 30%-50%. A number of evidence-based recommendations regarding the perioperative management of atrial fibrillation (AF) have been released from leading cardiovascular societies in recent years; however, it is unknown how closely these guidelines are being followed by medical practitioners. In addition, many of these society recommendations are based on patient stratification into "normal" and "elevated" risk groups for AF, but criteria for that stratification have not been clearly defined. In an effort to improve the perioperative management of AF, the Society of Cardiovascular Anesthesiologists (SCA) Clinical Practice Improvement Committee developed a multidisciplinary Atrial Fibrillation Working Group that created a summary of current best practice based on a distillation of recent guidelines from professional societies involved in the care of cardiac surgical patients. An evidence-based set of survey questions was then generated to describe the current practice of perioperative AF management. Through collaboration with the European Association of Cardiothoracic Anaesthetists (EACTA), that survey was distributed to the combined memberships of both the SCA and EACTA, yielding 641 responses and resulting in the most comprehensive understanding to date of perioperative AF management in North America, Europe, and beyond. The survey data demonstrated the broad range of therapies utilized for the prevention and treatment of poAF, as well as a spectrum of adherence to published guidelines. With the goal of improving adherence, a graphical advisory tool was created with an easily accessible format that could be utilized for bedside management. Finally, given that no evidence-based threshold currently exists to differentiate patients at normal risk to develop poAF from those at elevated risk, the SCA/EACTA AF working group created a list of poAF risk factors using expert opinion and based on published risk score models for poAF. This approach allows stratification of patients into risk groups and facilitates adherence to the evidence-based recommendations summarized in the graphical advisory tool. It is our hope that these new additions to the clinical toolkit for the management of perioperative AF will improve the evidence-based care and outcomes of cardiac surgical patients worldwide.
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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 | 0.016 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".