Need for Ongoing Anti Arrhythmic Drugs After Ablation of Atrial Fibrillation. Review
Bibliographic record
Abstract
Ablation of atrial fibrillation (AF) is increasingly common. Newer techniques have been developed and indications broadened to a greater number of patients with drug-resistant AF. The first end point of ablation is to cure AF without further need for Anti Arrhythmic Drugs (AADs), but the success rate at 1 year and over, after a single procedure, though higher than the success rate of AADs alone, is not 100% yet. The aim of the present work is to understand the added value of a persistent administration of previously ineffective AADs on the long-term success rate and to evaluate the timing of AADs suspension after ablation in different types of FA, when patients are in constant sinus rhythm after several months. The reduction of symptoms and the fear of asymptomatic recurrences of AF make physicians reluctant to discontinue AADs at the end of the blanking period, though the efficacy of AADs as a permanent solution late after procedure, to increase the sinus rhythm maintenance rate, is still a matter of ongoing debate. At the time, every patient undergoing ablation of AF should be assessed individually about the need to suspend AADs or not. To do this, good knowledge of AF recurrence predictors and long term success rates of AF ablation in specific clinical settings is essential. Loop Recorder as well is very useful in guiding the administration of AADs in a patient-tailored manner. Larger registries and controlled clinical trials in well-defined clinical settings are required to further elucidate the effects of a prolonged action of AADs after AF ablation. The article presented a short discussion of recent patents related to Anti Arrhythmic Drugs.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".