Interatrial block as a predictor of atrial fibrillation in patients with ST‐segment elevation myocardial infarction
Bibliographic record
Abstract
INTRODUCTION: Interatrial block (IAB) is strongly associated with recurrence of atrial fibrillation (AF) in different clinical scenarios. Atrial fibrosis is considered the responsible mechanism underlying the pathogenesis of IAB. The aim of this study was to investigate whether IAB predicted AF at 12 months follow-up in a population of patients with ST segment elevation myocardial infarction (STEMI). HYPOTHESIS: We aimed to investigate whether IAB predicted AF at 12 months follow up in a population of patients with STEMI. METHODS: Prospective, single center, observational study of patients presenting with ST-segment elevation myocardial infarction (STEMI) and referred to primary percutaneous coronary intervention (P-PCI). Surface electrocardiograms (ECG) were recorded on admission and at 6th hour post P-PCI. Patients were screened for the occurrence of AF at a 12-months visit. RESULTS: A total of 198 patients were included between September 2015 and September 2016. IAB (partial and advanced) was detected in 102 (51.5%) patients on admission. Remodeling of the P-wave and subsequent normalization reduced the prevalence of IAB to 47 (23.7%) patients at 6th hour. AF was detected in 17.7% of study patients at 12 months. Partial IAB (p-IAB) on admission (OR 5.10; 95% CI, 1.46-17.8; P = 0.011) and on 6th hour (OR 4.15; 95% CI, 1.29-13.4; P = 0.017), presence of a lesion in more than one coronary artery (OR 3.29; 95% CI, 1.32-8.16; P = 0.010) found to be independent predictors of AF at 12 months. CONCLUSION: IAB is common in patients with STEMI and along with the presence of diffuse coronary artery disease is associated with new onset of AF.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".