A predictive model for poor outcome of lower extremity motor function after acute ischemic stroke
10.3760/cma.j.issn.1673-4165.2025.03.002
- VernacularTitle:急性缺血性卒中后下肢运动功能转归不良的预测模型
- Author:
Shuang XU
1
;
Liming LU
;
Zhaowei LI
Author Information
1. 广州中医药大学体育健康学院，广州 510006
- Keywords:
Ischemic stroke;
Lower extremity;
Recovery of function;
Walking;
Treatment outcome;
Risk factors;
Nomograms
- From:
International Journal of Cerebrovascular Diseases
2025;33(3):168-172
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To develop and evaluate a nomogram prediction model for poor outcome of lower extremity motor function in patients with acute ischemic stroke (AIS) at 90 days after onset.Methods:Patients with AIS admitted to Guangzhou Province Hospital of Chinese Medicine from January to October 2024 were included retrospectively. At 90 days after onset, Functional Ambulation Category (FAC) was used for outcome evaluation. ≥4 was defined as good outcome and <4 was defined as poor outcome. Multivariate logistic regression analysis was used to identify the independent predictive factors for poor outcome of lower extremity motor function, and develop a nomogram prediction model. The area under the receiver operating characteristic curve, calibration curve, and clinical decision curve were used to evaluate the predictive model. Results:A total of 325 patients with AIS were enrolled, including 214 males (65.8%), median aged 62 years (interquartile range, 54-71 years); 158 patients (48.6%) had poor outcome of lower extremity motor function. Multivariate logistic regression analysis showed that older age (odds ratio [ OR] 1.037, 95% confidence interval [ CI] 1.011-1.065]; P=0.007) and a higher baseline National Institutes of Health Stroke Scale (NIHSS) score ( OR 1.472, 95% CI 1.336-1.637; P<0.001) were the independent predictors of poor outcome, while intravenous thrombolysis ( OR 0.195, 95% CI 0.080-0.443; P<0.001) and early rehabilitation intervention ( OR 0.444, 95% CI 0.231-0.850; P=0.014) were the independent predictors of good outcome. The area under the receiver operating characteristic curve of the nomogram prediction model developed using the above factors was 0.906 (95% CI 0.872-0.940), indicating that the model had good discriminability. The calibration curve fits well with the ideal curve. The clinical decision curve showed that the model had stronger clinical practicality. Conclusion:The nomogram developed by age, intravenous thrombolysis, early rehabilitation intervention, and baseline NIHSS score can effectively predict the risk of poor outcome of lower extremity motor function in patients with AIS and has higher clinical value.
