Integrating left atrial appendage morphology and lipoprotein(a) improves thrombus risk stratification in atrial...

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 CHA₂DS₂‑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, CHA₂DS₂‑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 CHA₂DS₂‑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 CHA₂DS₂‑VA score alone.