A Population-Based Study of Unexplained/Lone Atrial Fibrillation: Temporal Trends, Management, and Outcomes
Bibliographic record
Abstract
Background Previous studies on lone/unexplained atrial fibrillation and atrial flutter (AF) did not exclude patients with contemporary secondary AF triggers. We characterized unexplained AF using a strict definition, and compared it to secondary AF. Methods In this population-based study, unexplained AF was defined by the lack of any identifiable triggering medical/surgical diagnosis. Comparisons by AF type (unexplained vs secondary), age-of-onset (≤ / > 65 years), and sex were undertaken. Data were acquired by linking 6 population databases maintained by the Alberta Ministry of Health over a 9-year period (April 2006 to March 2015). The primary composite outcome of stroke, transient ischemic attack, thromboembolism, and/or death was assessed. Results There were 33,150 incident AF diagnoses identified, including 1145 patients (3.5%) with unexplained AF, 931 (81.2%) of whom were aged ≤ 65 years (2.8% of diagnoses, and 79% male). Patients with unexplained AF less often received rate/rhythm-control drugs ( P < 0.0001), but they more often underwent electrical cardioversion ( P < 0.0001) vs secondary AF patients. Men were younger at unexplained AF diagnosis (45 [interquartile range: 34-59] vs 58 [interquartile range: 40-69] years; P < 0.001). After adjusting for age at diagnosis, there were no sex-based differences in the primary outcome. Event-free survival in young unexplained AF (age ≤ 65 years) was 99.4% at 1 year and 98.3% at 3 years. At 3 years, hospitalization(s)/emergency visit(s) for noncardiovascular reasons and for AF occurred in 56.6% and 23.8% of these patients, respectively. Conclusions Using a strict contemporary definition of unexplained AF, this study shows that the condition is rare, predominantly male, and has excellent event-free survival. However, the high rate of acute hospital utilization after diagnosis is concerning.
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) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".