Prediction of in-hospital death following acute type A aortic dissection - Chen, Junquan; Bai, Yunpeng; Liu, Hong; Qin, Mingzhen; Guo, Zhigang (Frontiers in Public Health, 2023)
Background: We aimed to develop a prediction model for in-hospital death in Chinese patients with Acute type A aortic dissection (ATAAD). Methods: A total of 340 ATAAD patients from the Tianjin Chest Hospital data set formed a cohort. We applied least absolute shrinkage and selection operator analysis for variable selection and logistic regression coefficients for risk scoring. We classified patients into low-, middle-, and high-risk categorizations and investigated the association with in-hospital death. We developed a risk classifier based on independent baseline variables using a multivariable logistic model. Results: Based on risk scores weighted by 5 preoperative selected variables, we developed a risk prediction model AUC: 0.7039 [95% CI, 0.643-0.765]). We then classified patients as low, intermediate, and high risk in the cohort. With reference to the low-risk group, the intermediate- and high-risk groups conferred significantly higher in hospital death risks (adjusted OR: 3.973 [95% CI, 1.496-10.552], P<0.01; 8.280 [95% CI, 3.054-22.448], P<0.01, respectively). Conclusions: A risk classifier is a reliable prediction model for in-hospital death in patients with ATAAD