Abstract 1738: Lone Atrial Fibrillation: Long-Term Clinical and Echocardiographic Follow-up from the Canadian Registry of Atrial Fibrillation
Bibliographic record
Abstract
Background: The natural history of lone atrial fibrillation (AF) is unclear with conflicting data in the literature. We aimed to better describe the clinical outcomes and echocardiographic changes associated with lone AF. Methods: The Canadian Registry of Atrial Fibrillation (CARAF) enrolled 803 non-surgical and non-flutter patients with new onset AF between 1990 and 1996. At enrollment, patients were classified as lone AF (LAF) or not lone AF (Not LAF) based on structural heart disease or hyperthyroidism. Clinical data was prospectively collected with follow-up at 3 months, 1 year, then annually; echocardiograms were performed at enrollment and years 2, 4, and 7. Results: The LAF group (n=212) had a median age of 57 (1 st quartile 44, 3 rd quartile 67) while the Not LAF group (n=591) had a median age of 67 (59, 73), p<0.0001. During the median follow-up of 8 years in the LAF group and 7 years in the Not LAF group, there was a significant difference in survival free from stroke or embolism favoring the LAF group (Figure ). At 8 years, the probability of remaining free of chronic AF was 78.8% vs 69.3% (p=0.02) and free of symptomatic or documented recurrence of AF was 40.1% vs 26.9% (p<0.01) in the LAF vs Not LAF group. The LAF group had smaller LV diastolic and systolic dimensions by 5.5% and 10.2%, respectively, vs the Not LAF group (p<0.0001). The LV mass was smaller at baseline by 21.1% (p<0.0001) vs the Not LAF group, but increased at a greater rate (4.0% vs 0.9%/2 years, p<0.0001). Conclusions: Lone AF, compared to non-lone AF, is associated with a lower rate of death, stroke or embolism, recurrence and progression to chronic AF. Interestingly, LV mass increased significantly only in the Lone AF group.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".