Update on the Association of Inflammation and Atrial Fibrillation
Bibliographic record
Abstract
Atrial fibrillation (AF) is a common arrhythmia and is associated with significant morbidity and mortality. The pathogenesis of AF remains incompletely understood and management remains a difficult task. Over the past decade there has been accumulating evidence implicating inflammation in the pathogenesis of AF. Inflammation appears to play a significant role in the initiation and perpetuation of AF as well as the prothrombotic state associated with AF. Inflammatory biomarkers (C-reactive protein and interleukin-6) have been shown to be associated with the future development, recurrence and burden of AF, and the likelihood of successful cardioversion. Therapies directed at attenuating the inflammatory burden appear promising. Animal and clinical studies have evaluated statins, angiotensin-converting enzyme inhibitors/angiotensin-II receptor blockers, and corticosteroids for the treatment or prevention of AF. The purpose of this review is to provide current evidence on the relationship between inflammation and AF and potential therapies available to modulate the inflammatory state in AF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".