Left atrial appendage morphology and hemodynamics: potential new markers for individualized thromboembolic risk assessment in atrial fibrillation

Background Traditional CHA₂DS₂-VASc scoring has well-recognized limitations in thromboembolic risk assessment for atrial fibrillation (AF), particularly in low-score patients who nevertheless thrombose, high-score event-free individuals, cancer patients, and post-ablation cohorts. The left atrial appendage (LAA) is the source of 98% of thrombi in non-valvular AF and exhibits marked inter-individual morphological and hemodynamic variability that traditional scores completely ignore. Aims This narrative review critically evaluates current evidence on LAA morphology, hemodynamics, computational fluid dynamics/fluid-structure interaction (CFD/FSI) studies, and digital twin technology, and proposes a mechanism-driven, individualized risk assessment framework for AF-related thromboembolism. Methods A literature search was conducted in PubMed/MEDLINE and Web of Science (1990–May 2026) using combinations of keywords related to LAA morphology, hemodynamics, AF, and thromboembolism. Priority was given to landmark original studies, high-quality observational studies with multivariable adjustment, meta-analyses, and contemporary CFD/digital twin studies. A narrative synthesis was adopted owing to heterogeneity in study designs and outcomes. Results LAA morphological subtypes are associated with long-term stroke risk, with chicken-wing being protective (OR 0.21, 95% CI 0.05–0.91) and cauliflower carrying the highest risk (OR 8.02, 95% CI 0.92–27.86). However, risk is highly context-dependent, with chicken-wing unexpectedly increasing peri-ablation thromboembolic risk (OR 7.2, 95% CI 1.35–38.33) and windsock morphology independently predicting post-ablation AF recurrence (OR 2.72, 95% CI 1.21–6.12). Importantly, traditional morphological classification does not correlate directly with blood stasis ( p = 0.365), whereas quantitative geometric parameters such as trabecular number, normalized stroke volume, and ostial area are far more sensitive predictors (R² = 74%). Digital twins integrating multimodal clinical, morphological, and hemodynamic data identify a high-risk phenogroup with a 70% thrombus history rate. Conclusion Based on these findings, we propose a practical two-tier assessment framework combining basic morphological classification with multimodal refined evaluation (digital twin) for intermediate-/high-risk or clinically challenging cases. This framework represents a paradigm shift from static clinical scores toward mechanism-driven, individualized risk management. Prospective validation of this approach is now warranted.