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Establishment and evaluation of risk prediction model for ischemic stroke after coronary artery bypass grafting in elderly patients / 中华胸心血管外科杂志
Article en Zh | WPRIM | ID: wpr-1029692
Biblioteca responsable: WPRO
ABSTRACT
Objective:To explore the risk factors of ischemic stroke after coronary artery bypass grafting(CABG) in elderly(≥75 years old)patients, establish a risk prediction model and evaluate it.Methods:From January 2015 to September 2021, a total of 1 553 elderly patients with coronary artery disease who were admitted to Beijing Anzhen Hospital for coronary artery bypass grafting were included retrospectively. Among which 1 121(72%) cases were males, with a median age of 77( IQR 75, 78) years. Clinical data were collected and univariate analysis and multiple logistic regression analysis were used to explore the risk factors of ischemic stroke after CABG in elderly patients. After the establishment of risk prediction model, we constructed the nomogram, and tested the discrimination and calibration of the model. Results:All patients underwent CABG, there were 35 patients with ischemic stroke after operation, with an incidence of 2.25%(35/1 553). Multivariate logistic regression analysis showed that diabetes( OR=2.61, 95% CI: 1.31-5.32), old myocardial infarction( OR=3.62, 95% CI: 1.61-7.63), systolic blood pressure( OR=1.03, 95% CI: 1.01-1.04) and vertebral artery stenosis( OR=1.01, 95% CI: 1.00-1.02) were independent risk factors for postoperative cerebral infarction in patients undergoing CABG. The model was presented by a nomogram, and the model discrimination was evaluated by ROC curve. The area under the curve( AUC) was 0.757, indicating a optimal discrimination. Hosmer- Lemeshow test of goodness of fit was performed to evaluate the model calibration( χ2=6.209, P=0.624). Conclusion:Diabetes mellitus, old myocardial infarction, systolic blood pressure and vertebral artery stenosis are independent risk factors for ischemic stroke in elderly patients after CABG. The established risk prediction model has optimal discrimination and calibration.
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Texto completo: 1 Banco de datos: WPRIM Idioma: Zh Año: 2023 Tipo del documento: Article
Texto completo: 1 Banco de datos: WPRIM Idioma: Zh Año: 2023 Tipo del documento: Article