A nomogram prediction model for poor outcome in patients with minor ischemic stroke
10.3760/cma.j.issn.1673-4165.2024.04.001
- VernacularTitle:轻型缺血性卒中患者转归不良的列线图预测模型
- Author:
Chenchen LI
1
;
Jiaxuan LI
;
Ziwei CAO
;
Xiaolu HE
;
Xiangzhu FAN
;
Chi ZHANG
Author Information
1. 安徽医科大学附属合肥医院神经内科，合肥 230011
- Keywords:
Ischemic stroke;
Severity of illness index;
Treatment outcome;
Risk factors;
Nomograms
- From:
International Journal of Cerebrovascular Diseases
2024;32(4):241-246
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To develop and evaluate a nomogram prediction model for poor outcome in patients with minor acute ischemic stroke (MIS) at 90 days after onset.Methods:Patients with MIS admitted to the Second People's Hospital of Hefei from January 2022 to June 2023 were retrospectively enrolled. At 90 days after onset, the modified Rankin Scale was used for outcome evaluation. <2 points were defined as good outcome and ≥2 points were defined as poor outcome. Multivariate logistic regression analysis was used to identify independent risk factors for poor outcome, and a nomogram prediction model was developed based on these factors. Results:A total of 177 patients with MIS were included, of which 61 (34.46%) had poor outcome. Multivariate logistic regression analysis showed that hypertension (odds ratio [ OR] 3.484, 95% confidence interval [ CI] 1.378-8.810; P=0.008), diabetes ( OR 2.936, 95% CI 1.301-6.625; P=0.009), National Institutes of Health Stroke Scale (NIHSS) score at admission ( OR 2.936, 95% CI 1.027-1.709; P=0.031) and systolic blood pressure at admission ( OR 1.083, 95% CI 1.053-1.115; P<0.001) were the independent risk factors for poor outcome. The established nomogram prediction model had a C-index of 0.828 and the area under the curve was 0.841 (95% CI 0.778-0.891). The calibration curve fitted well with the ideal curve. The clinical decision curve showed that the model had stronger clinical applicability. Conclusions:Hypertension, diabetes, NIHSS score and systolic blood pressure at admission are independent risk factors for poor outcome of patients with MIS. The nomogram based on the above factors has higher discriminative power and clinical value for predicting poor outcome in patients with MIS.
