Related Experiment Video
Updated: Aug 24, 2026
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
A multi-parameter predictive model incorporating VEGF for asymptomatic cerebral infarction after RFCA in atrial
Siliang Han1,2, Chunhong Chen2, Zhe Wang2
1The Second Affiliated Hospital of Hebei Medical University, Shi Jiazhuang, Hebei, China.
Background:
Asymptomatic cerebral infarction (ACI) is a frequent yet under-recognized complication following radiofrequency catheter ablation (RFCA) in patients with atrial fibrillation (AF). Early identification of patients at risk remains challenging, particularly in the absence of clinically overt neurological symptoms. This study aimed to develop a multi-parameter predictive model integrating clinical, procedural, and biomarker-based factors, with a particular focus on vascular endothelial growth factor (VEGF).
Methods:
This retrospective cohort study included 300 consecutive AF patients undergoing first-time RFCA. Brain magnetic resonance imaging was performed within 24-72 h post-procedure to detect ACI. Clinical, procedural, and laboratory data were systematically collected. Serum VEGF levels were measured using an enzyme-linked immunosorbent assay. Univariable and multivariable logistic regression analyses were conducted to identify independent predictors of ACI. Model performance was evaluated using receiver operating characteristic (ROC) analysis.
Results:
ACI was detected in 48 patients (16.0%). Patients with ACI were significantly older and had higher body mass index compared to those without ACI (p < 0.001). Serum VEGF levels were markedly elevated in the ACI group (350 ± 45 vs. 200 ± 30 pg/mL, p < 0.001). Multivariable analysis identified age (OR: 1.08, p = 0.01), BMI (OR: 1.15, p = 0.003), and VEGF (OR: 1.02, p < 0.001) as independent predictors. The predictive model demonstrated good discriminative ability with an AUC of 0.82. Additionally, RFCA was associated with significant improvements in cardiac function and autonomic regulation (p < 0.001).
Conclusion:
ACI remains a clinically relevant complication following RFCA. A predictive model incorporating VEGF alongside clinical factors provides improved risk stratification. These findings highlight the importance of endothelial dysfunction in ACI pathogenesis and support the integration of biomarkers into clinical decision-making.