Cardiovascular Outcomes With an Early Rhythm Control Strategy in Atrial Fibrillation: A Systematic Review
Bibliographic record
Abstract
In practice, atrial fibrillation (AF) is typically managed by controlling ventricular rate given similar long-term outcomes and a more tolerable drug profile when compared to rhythm control. However, despite treatment via rate control, patients remain at increased risk for cardiovascular complications. This systematic review provides a summary of literature evaluating the effectiveness of early rhythm control (ERC, initiated within 2 years of diagnosis) in AF in reducing cardiovascular complications. A systematic review utilizing the MEDLINE, EMBASE, and the Cochrane Database of Systematic Reviews was performed to identify literature evaluating effectiveness of rhythm control strategies and cardiovascular complication reduction rates in ERC. A total of three literature articles meeting the inclusion and exclusion criteria were included for evaluating the benefit of ERC. One of these examined was a trial that directly compared antiarrhythmic drug (AAD) versus catheter ablation (CA) therapy in maintenance of sinus rhythm (SR). This systematic review shows that ERC is associated with a reduction of cardiovascular events in AF patients compared to other treatment strategies.
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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".