Postoperative Atrial Fibrillation: Role of Inflammatory Biomarkers and Use of Colchicine for Its Prevention
Bibliographic record
Abstract
Postoperative atrial fibrillation (POAF) is the most common complication following cardiac surgery, occurring in up to 65% of cardiac surgical patients. It is a condition associated with increased morbidity, increased length of hospital stay, and increased health care costs. One of the many potential causes of POAF is postsurgical inflammation, as demonstrated by increased levels of inflammatory biomarkers such as C-reactive protein and interleukin-6. Although still a subject of debate, the role of these inflammatory markers in the pathogenesis of POAF remains under vigorous investigation. Several antiinflammatory drugs have demonstrated promising results in prevention of POAF, including nonsteroidal antiinflammatory drugs, glucocorticoids, and statins. Colchicine is one of the oldest medications used in modern medicine, typically for the treatment and prevention of gout. New evidence has recently surfaced that colchicine may also be useful in the prevention of POAF. In recent studies, colchicine has demonstrated both safety and efficacy in the prevention of POAF. Several new studies are currently being initiated that may further elucidate colchicine's role in the prevention of POAF.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".