A risk model integrating LAA morphology and lipoprotein(a) significantly outperformed the CHA2DS2-VA score for thrombus risk discrimination in atrial fibrillation (AUC 0.861 vs 0.643; p<0.0001).
Cohort (n=418)
Does a risk model integrating LAA morphology and lipoprotein(a) improve thrombus risk stratification in patients with atrial fibrillation compared to the CHA2DS2-VA score alone?
Integrating left atrial appendage morphology and lipoprotein(a) with clinical factors significantly improves thrombus risk stratification in atrial fibrillation compared to the CHA2DS2-VA score alone.
Effect estimate: ΔAUC 0.2186 (95% CI 0.829–0.892)
Absolute Event Rate: 0.861% vs 0.643%
p-value: p=< 0.0001
Accurate assessment of thrombus risk in atrial fibrillation (AF) requires the integration of structural and metabolic factors, which are insufficiently addressed by current clinical risk scores. We developed a model that added LAA morphology and metabolic markers, and compared it with the CHA 2 DS 2 ‑VA score. This retrospective cohort study included 418 participants (262 AF patients without thrombus and 156 AF patients with thrombus). Data on medical history, contrast‑enhanced computed tomography with three‑dimensional reconstruction, and metabolic profiling were retrospectively collected. The final model comprised six independent predictors: non‑paroxysmal AF, CHA 2 DS 2 ‑VA score ≥ 2, anticoagulation use, AF duration, LAA orifice ellipticity index (LAA OEI), and lipoprotein(a) (Lp(a)). The model demonstrated excellent discrimination (AUC = 0.861, 95% CI 0.829–0.892) and good calibration (Hosmer‑Lemeshow test p = 0.462). It significantly outperformed the CHA 2 DS 2 ‑VA score (AUC = 0.643; ΔAUC = 0.2186; p < 0.0001), with a net reclassification improvement of 0.844 (p < 0.001) and an integrated discrimination improvement of 0.311 (p < 0.001). Integrating LAA OEI and Lp(a) with clinical factors improves thrombus risk stratification in patients with AF compared with the CHA 2 DS 2 ‑VA score alone.
Song et al. (Tue,) conducted a cohort in Atrial fibrillation (n=418). Risk model integrating LAA morphology and lipoprotein(a) with clinical factors vs. CHA2DS2-VA score was evaluated on Thrombus risk discrimination (AUC) (ΔAUC 0.2186, 95% CI 0.829–0.892, p=< 0.0001). A risk model integrating LAA morphology and lipoprotein(a) significantly outperformed the CHA2DS2-VA score for thrombus risk discrimination in atrial fibrillation (AUC 0.861 vs 0.643; p<0.0001).