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Updated: May 31, 2026
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
Development and validation of a prediction model for ischemic stroke recurrence risk in patients with ischemic stroke
Rongxing Qin1, Xiaoying Huang2, Qinchun Qin1
1Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Guangxi Zhuang Autonomous Region, Nanning, 530021, China.
Background:
The recurrence rate of atrial fibrillation (AF)-related ischemic stroke (IS) remains persistently high, significantly increasing patient mortality, disability, and socioeconomic burden. This underscores an urgent need for a practical tool to predict long-term recurrence risk. This study aimed to investigate the key risk factors for recurrent IS in patients with AF and IS, and to construct and validate a recurrence risk prediction model using LASSO regression.
Methods:
We retrospectively enrolled 113 patients with AF complicated by IS between 2017 and 2024, with a follow-up period of up to 7 years. LASSO regression was employed to screen predictive factors and develop a risk model. The model's performance was evaluated using the concordance index (C-index) and the area under the receiver operating characteristic curve (AUC). A restricted cubic spline analysis was conducted to examine the non-linear relationship between age and the risk of recurrent IS. Subgroup analyses were performed using Cox regression models.
Results:
During the 7-year follow-up, recurrent IS occurred in 45.13% of patients. The LASSO regression-based prediction model, incorporating 19 predictive factors, demonstrated high predictive power with an AUC of 0.917. Furthermore, the model's predictive ability improved over time, achieving a C-index of 0.760 at the seventh year of follow-up. A significant non-linear relationship was identified between age and recurrence risk.
Conclusion:
A LASSO-derived model accurately estimates the long-term risk of recurrent IS after AF-related stroke. Age has a non-linear influence on recurrence, and the efficacy of anticoagulation may be modified by smoking status. These findings support the development of individualized prevention strategies.