Abstract P640: Incident Atrial Fibrillation and Cardiovascular Risk Increases in Patients With Increased Burden of Atrial Ectopy
Bibliographic record
Abstract
Introduction: Atrial fibrillation (AF) is a major risk factor for cerebral ischemia in North America. Atrial ectopy has been associated with incident AF and increased stroke risk on short-duration ECG monitoring. The objective of this study was to characterize the relationship between the burden of atrial ectopy with future AF, stroke, and cardiovascular events on prolonged ECG monitoring. Methods: A retrospective, observational study was conducted at a single centre enrolling patients >18 years old referred from TIA clinic. Data was collected from 7- and 14-day Holter monitor reports, patient charts, and cardiac investigations. The final sample included 1124 patients; a subgroup of 759 patients had echocardiograms. Univariate and multivariate logistic regression determined the odds ratio (OR) of developing the composite outcome (AF, TIA/stroke, ACS, death) or secondary outcomes (AF or TIA/stroke). Results: The population was high-risk with a mean CHA 2 DS 2 -VASc of 4.0 (±1.8); during 1-year of follow-up, the primary outcome occurred amongst 116 (10.3%) patients. Univariate analysis ORs are displayed in Table 1. There was a statistically significant relationship (p<0.001) between percentage of PACs and the composite outcome (OR 4.066), and AF (11.886) for patients with 2-5% PACs. PAC runs/day was significant if >5/day for AF (OR 5.989, p<0.01) and for the composite (OR 2.231, p<0.05). Long PAC runs (>30 beats) also had significant ORs for AF (2.849, p<0.01) and the composite (5.320, p<0.01). In the subgroup analysis, reduced ejection fraction had an OR of 2.172 (1.407-5.771) for the composite outcome, and atrial dilatation had an OR of 2.778 (1.390-5.551) for AF. Conclusions: Increased burden of atrial ectopy is associated with increased odds of developing AF and a composite of cardiovascular events. Patients with increased ectopy should be considered for further, future ECG monitoring and risk stratification with echocardiogram.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".