1356Value of interatrial block for the prediction of silent ischemic brain lesions
Bibliographic record
Abstract
Introduction: Previous studies demonstrated that interatrial block (IAB) is associated with atrial fibrillation (AF) in different clinical scenarios. The aim of our study was to determine whether IAB could predict silent ischemic brain lesions (sIBL), detected by magnetic resonance imaging (MRI). Methods: The study group consisted in123 patients (36% male) who had presented to the neurology outpatient clinic and had brain MRI performed within 7 days. Patients were asymptomatic in terms of stroke-like symptoms. A 12-lead surface ECG was obtained from each patient. IAB was defined as P-wave duration >120 ms with (advanced IAB) or without (partial IAB) biphasic morphology in the inferior leads. Results: sIBL was detected in 61 patients. Patients with sIBL were older (P<0.001), have more left ventricular hypertrophy (LVH) (P=0.02) and higher CHA2DS2-VASc score compared to those without (P<0.001). P-wave duration was significantly longer in patients with sIBL (124 [110.5–129] msvs 107 [102–116.3] ms) (P<0.001). IAB was diagnosed in 36 patients (59%) with sIBL (+) and in 11 patients (18%) with sIBL (−); p<0.001. Multivariate Cox regression analysis identified age [Odds ratio (OR), 1.061; 95% confidence interval (CI), 1.012 - 1.113; p=0.014], CHA2DS2-VASc score (OR, 1.758; 95% CI, 1.045 - 2.956; p=0.034), LVH (OR, 3.062; 95% CI, 1.161 - 8.076; p=0.024) and presence of IAB (including both partial and advanced) (OR, 5.959; 95% CI, 2.269 - 15.653; p<0.001) as independent predictors of sIBL.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".