Abstract 9675: Does the Degree of Left Ventricular Dysfunction or Symptom Status Influence the Risk of Stroke or Systemic Embolism Among Patients With Atrial Fibrillation and Heart Failure?-Results From the ACTIVE Study
Bibliographic record
Abstract
Background: Heart failure (HF) is a major component of widely applied stroke risk stratification schemes in atrial fibrillation (AF). However, data regarding the relationship between left ventricular (LV) dysfunction or HF symptoms and risk of stroke/systemic embolism among HF patients remains sparse. Methods: A total of 3487 participants from the Atrial Fibrillation Clopidogrel Trial with Irbesartan for Prevention of Vascular Events (ACTIVE) trials with HF at baseline were randomized to anti-platelet therapy. Patients with HF were categorized as having preserved vs reduced ejection fraction (PEF ≥ 0.50, REF < 0.50). If reduced, the degree of LV dysfunction was classified as mild, moderate or severe. HF symptoms were assessed using New York Heart Association (NYHA) class I-IV. Cox proportional-hazards models were used to estimate hazard ratios (HR, 95% CI) for stroke/systemic embolism across categories of LV dysfunction and NYHA class. Results: At baseline, 875 (47%) had HF-PEF, 982 (53%) had HF-REF; the degree of LV dysfunction was classified as mild in 25%, moderate in 25% and severe in 14%. During 3.6 years of follow-up, 211 patients had stroke/systemic embolism. In multivariable analysis, independent predictors of stroke were age ≥ 75 years (HR 2.83, 1.80-4.44), diabetes (HR 1.45, 1.03-2.03), diastolic blood pressure (per 1 mmHg, HR 1.02, 1.01-1.04), peripheral arterial disease(HR 1.94, 1.10-3.41), female(HR 1.48, 1.07-2.05) and prior stroke/transient ischemic attack (HR 1.77, 1.23-2.54) however EF < 0.50, LV dysfunction or NYHA class were not predictors. Compared to those with HF-REF, patients with HF-PEF exhibited similar risk of stroke/systemic embolism: 4.18% vs. 3.83% per year, HR 0.89, 95% CI 0.65-1.22 after controlling for AF risk factors. Compared to normal LV function, there was no significant trend across categories of LV systolic dysfunction (p for trend, 0.57). The risk of stroke/systemic embolism was similar in HF patients with NYHA class I (4.0% per year, referent category), II (4.0%, HR 0.87, 0.60-1.26), III (3.9%, HR 0.62, 0.38-1.02), or IV (2.8%, 0.60, 0.14-2.55). Conclusion: Among patients with a history of HF, the presence or absence of LV dysfunction or severity of HF symptoms did not influence the risk of stroke/systemic embolism.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".