E/eʹ ratio and left atrial area are predictors of atrial fibrillation in patients with hypertrophic cardiomyopathy
Bibliographic record
Abstract
INTRODUCTION: Atrial fibrillation (AF) occurs in about 20%-25% of patients with hypertrophic cardiomyopathy and is associated with increased risk of cardioembolism and heart failure impacting on patients' morbidity and mortality. The aim of this study was to identify echocardiographic predictors of AF in a cohort of patients with hypertrophic cardiomyopathy (HCM). METHODS: Patients were recruited from 2 centers: Buenos Aires Cardiovascular Institute and the Hospital Vall d'Hebron of Barcelona which were analyzed together. Retrospective study using electronic charts. RESULTS: A total of 321 patients with HCM and no documented history of AF were included. Median follow-up was 3 years. Mean age was 54 ± 16 years. Obstructive HCM was present in 41% of the patients, and 94.2% had preserved systolic function. Thirty-eight patients developed AF during the follow-up period (11.8%). Univariate analysis showed that age, maximum myocardial thickness, atrial area, an E/e' ratio ≥ 17, and systolic pulmonary pressure estimated by echocardiography were associated with new-onset AF. Multivariate analysis showed that E/e' ≥ 17 ratio {HR 3.27 ([1.10-9.27] P = .033)} and atrial area {HR 1.06 ([1.01-1.13] P = .037)} remained predictors of AF. CONCLUSIONS: are strong predictors of AF in patients with HCM.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".