Familial clustering of lone atrial fibrillation in patients with saddleback-type ST-segment elevation in right precordial leads
Bibliographic record
Abstract
AIMS: We recently identified a large family with a high prevalence of lone atrial fibrillation (AF) and saddleback-type ST-segment elevation in leads V(1-3), without a history of ventricular arrhythmias or syncope. On the basis of this finding, we studied whether there is a relationship between saddleback ST-elevation and lone AF. METHODS AND RESULTS: We examined 168 (mean age 50+/-8 years, 130 males) lone AF patients and 541 (mean age 50+/-6 years, 274 males) healthy subjects. The prevalence of saddleback ST-elevation was higher in the lone AF group than the control group (10 vs. 0.4%, P<0.001). None had a coved-type ST-elevation in baseline ECG or during drug challenge with ajmaline or flecainide (n=13), a family history of sudden cardiac death, ventricular tachyarrhythmias, syncope, or any other features diagnostic to the Brugada syndrome. Familial clustering of lone AF (i.e. AF in >30% of first-degree relatives) was more common among the subjects with saddleback ST-elevation (24 vs. 7%, P=0.03). CONCLUSION: Saddleback-type ST-segment elevation is a relatively common finding among patients with lone AF. The familial clustering of the disorder indicates that genetic factors may be involved in the pathogenesis of the ECG abnormality and lone AF in these patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".