Construction of a biomarker-based prediction model for neural function after acute Stanford type A aortic dissection
SI Yi
SHI Heng
XUE Chao
WANG Weiguang
ZHANG Jinglong
YANG Chen
WANG Dongxu
ZHU Hanzhao
ZHANG Bin
SUN Jingwei
JIN Zhenxiao
LIU Zhiheng
DUAN Weixun
Abstract：Objective To construct a clinical model for predicting postoperative neurological prognosis in patients with acute Stanford type A aortic dissection(AAAD)through preoperative serum markers and baseline characteristics of AAAD patients.Methods The study included AAAD patients in Xijing Hospital,Air Force Medical University from January 2000 to May 2021.After excluding patients who were not examined after admission and whose relevant data were incomplete,they were divided into two groups according to whether there were neurological complications after surgery(n=113)and no neurological complications(n=1 090).Through univariate and multivariate binary logistic regression analysis,predictors of postoperative neurological complications were screened from the entire data,and a nomogram based on preoperative relevant serum markers and clinical characteristics was constructed.In addition,internal validation,area under the receiver operating characteristic curve(AUC),and calibration curve were performed on the model to evaluate the discrimination ability of the model.Results Multivariate logistic regression analysis showed that BMI,D-dimer,creatinine,and troponin Ⅰ were associated with postoperative neurological complications,respectively.A nomogram was established based on the four variables validated internally by AUC 0.713.The calibration chart showed that the predicted and actual probability of postoperative neurological complications in internal validation could be well matched.Conclusion This nomogram can predict the possibility of postoperative neurological complications in patients with AAAD,and has good resolution and clinical application value.
Keywords：acute Stanford type A aortic dissectionnomogramneurological complications
Publication Date：2025-02-27
Online Publishing Date：2026-08-26(First online date of this platform, not the publication date of the document)
Pages：6( 192-197 )