Risk factors for malignant middle cerebral artery infarction and establishment of its risk prediction model
10.3760/cma.j.cn115354-20210227-00133
- VernacularTitle:恶性大脑中动脉梗死的危险因素分析及风险预测模型的构建
- Author:
Shasha FANG
1
;
Jie CHEN
;
Ruiming FAN
Author Information
1. 遵义医科大学附属医院神经内科，遵义 563000
- Keywords:
Large hemispheric infarction;
Malignant middle cerebral artery infarction;
Risk factor;
Nomogram model
- From:
Chinese Journal of Neuromedicine
2021;20(5):477-482
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the risk factors for malignant middle cerebral artery infarction (MMI) in patients with acute large hemispheric infarction (LHI), and construct a visual nomogram model with early prediction value.Methods:A total of 274 patients with acute LHI admitted to our hospital from January 2018 to June 2020 were chosen in our study; according to disease progression, these patients were divided into MMI group ( n=97) and non-MMI group ( n=177). The general information, laboratory examination indexes, imaging examination indexes of patients in the two groups were compared. The items with significant differences were included in multivariate Logistic regression analysis to identify the independent factors affecting the occurrence of MMI in LHI patients. R language was used to draw nomograms, and the model was evaluated and internally verified. Results:Multivariate Logistic regression analysis showed that National Institutes of Health stroke scale (NIHSS) scores, infarct volume, fever, thrombolysis, heart disease, and neutrophils count were independent risk factors for MMI after LHI ( P<0.05). Age is an independent protective factor for MMI after LHI. Based on these 7 factors, the nomogram model of the risk of MMI was drawn and verified, and the C-index was 0.905 ( 95%CI: 0.868-0.941) and the calibration was good. The area under receiver operating characteristic curve of the model for predicting MMI in LHI patients was 0.905 ( 95%CI: 0.868-0.941), suggesting that the histograph model had high efficiency in predicting MMI in LHI patients. Conclusion:Young LHI patients with high NIHSS scores, large infarct volume, high neutrophil count, fever, and heart disease, and those accepted thrombolytic therapy at admission have higher probability of MMI; the nomogram model, which can improve the diagnostic efficiency of MMI in LHI patients, has good predictive ability, good accuracy and discrimination in the study.
