The prediction of recurrent cerebral infarction by the neovascularization grade of carotid plaque using contrast enhanced ultrasonography: a Logistic regression model analysis / 中华医学超声杂志(电子版)
Chinese Journal of Medical Ultrasound (Electronic Edition)
; (12): 43-47, 2018.
Article
de Zh
| WPRIM
| ID: wpr-712056
Bibliothèque responsable:
WPRO
ABSTRACT
Objective To evaluate the utility of neovascularization grade of carotid plaque using contrast enhanced ultrasonography in the prediction of recurrent cerebral infarction by Logistic regression model analysis. Methods Eight-nine patients with first cerebral infarction were studied by conventional and contrast enhanced ultrasonography, then the two-dimensional echoic grade and neovascularization grade of carotid plaque was assessed. The condition of recurrent cerebral infarction in next year was followed up. The independent risk and predictive factors of recurrent cerebral infarction were analyzed by Logistic regression model and the utility of the independent risk and predictive factors in the prediction of recurrent cerebral infarction was evaluated by ROC curve. Results Both two-dimensional echoic grade of carotid plaque (P=0.028) and neovascularization grade of carotid plaque (P=0.006) were the risk and predictive factors of recurrent cerebral infarction in single-factor Logistic regression model. However, only the neovascularization grade of carotid plaque was the independent risk and predictive factor in multiple-factor Logistic regression model (P=0.043) with an OR value of 1.916. The sensitivity and specificity of the neovascularization grade of carotid plaque in prediction of recurrent cerebral infarction (cut-off value>Ⅱ) were 67.74% and 70.69% respectively and the area under ROC curve was 0.684(95%CI:0.577~0.779,P=0.0017).Conclusion The neovascularization grade of carotid plaques on contrast enhanced ultrasonography is the independent risk and predictive factor in prediction of recurrent cerebral infarction.
Texte intégral:
1
Indice:
WPRIM
Type d'étude:
Prognostic_studies
langue:
Zh
Texte intégral:
Chinese Journal of Medical Ultrasound (Electronic Edition)
Année:
2018
Type:
Article