The association of QRS duration with atrial fibrillation in a heart failure with preserved ejection fraction population: a pilot study
Bibliographic record
Abstract
BACKGROUND: Heart failure is a significant cause of morbidity and mortality, yet patient risk stratification may be difficult. Prevention or treatment of atrial fibrillation (AF) may be an important strategy in these patients that could positively affect their outcome. It has been demonstrated that in patients with systolic dysfunction, prolonged QRS duration (QRSd), an easily measured electrocardiographic parameter, is associated with AF. HYPOTHESIS: Prolonged QRSd is associated with an increase in prevalence of AF in patients with heart failure with preserved ejection fraction(HFPEF). METHODS: Between February 2006 and February 2009, 718 patients were discharged with a diagnosis of HF from the Dartmouth-Hitchcock Medical Center. Of these, 206 had EF ≥50% by echocardiography performed within 72 hours of admission. After exclusions, 82 patients remained, of which 25 had AF and 57 had sinus rhythm. Characteristics of the AF and sinus-rhythm patients were compared in this pilot study. RESULTS: After adjustment for age, prior diagnosis of HF, and left atrial area, there was a nonsignificant trend (odds ratio: 2.2, 95% CI of 0.3-17.2) for a QRSd >120 ms to be associated with AF. CONCLUSIONS: Similar to results in patients with systolic dysfunction, patients with preserved EF may have an association between a prolonged QRSd and 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".