Background: This study is to establish prediction tools for in-hospital rupture of type A aortic dissection (TAAD) patients, to better guide emergency surgical triage and patient counselling. Methods: We retrospectively evaluated 1,133 consecutive patients with TAAD from January 2010 to December 2016. The study population was divided into training and testing datasets in a 70:30 ratio for further analysis using Random Forest. Results: The Random Forest classification model was developed with the training dataset and 16 variables were confirmed as ‘important’: age, BMI, gender, syncope, lower limb numbness/pain, acute phase of the TAAD, BP >160 mmHg at admission; acute liver dysfunction, WBC >15×10⁹/L, aortic size, aortic height index (AHI), periaortic hematoma, pleural effusion, brachiocephalic artery involvement, renal artery involvement, and hemopericardium. Validation of the model showed good discrimination with an AUC, sensitivity, specificity, positive predictive value and negative predictive value of 0.994, 1.000, 0.987, 0.998 and 1.000, respectively, in the training dataset, and 0.752, 0.990, 0.514, 0.945 and 0.857, respectively, in the testing dataset. Conclusions: An easy-to-use tool to predict in-hospital rupture for TAAD patients was developed and validated (http://47.107.228.109/). Periaortic hematoma is the strongest predictor. Simple clinical information such as syncope can be very useful in in-hospital rupture risk stratification.

Background: It is well established that postoperative atrial fibrillation (POAF) is associated with adverse postoperative outcomes after major cardiac operations. The purpose of this study was to investigate the incidence of new‐onset POAF after successful total arch repair surgery and the association between POAF and in‐hospital mortality. Methods and Results: All consecutive patients undergoing total arch repair from September 2012 to December 2019 in Fuwai hospital were enrolled (n=1280). Patients diagnosed with preoperative atrial fibrillation were excluded. POAF was diagnosed as the new‐onset atrial fibrillation or flutter for more than 5 minutes based on continuous electrocardiogram monitoring. A logistic regression model was used to determine predictors of in‐hospital mortality. Multivariable adjustment, inverse probability of treatment weighting, and propensity score matching were used to adjust for confounders. POAF was diagnosed in 32.3% (411/1271) of this cohort population. The occurrence of new‐onset POAF was associated with age (odds ratio [OR], 1.05; 95% CI, 1.04–1.06; P <0.001), male sex (OR, 0.72; 95% CI, 0.52–0.98; P =0.035), and surgery duration (OR, 1.2; 95% CI, 1.12–1.28; P <0.001). The in‐hospital mortality was significantly higher in patients with POAF than those without POAF (10.7% versus 2.4%, P <0.001). Inverse probability of treatment weighting and propensity score matching analyses confirmed the results. The increased in‐hospital mortality in POAF group still existed among subgroup analysis based on different age, sex, hypertension, smoking, and hypokalemia, combined with cardiac surgery, and deep hypothermic circulatory arrest. Conclusions: More careful attention should be given to POAF after total arch repair surgery. The incidence of POAF after total arch repair surgery was 32.3% and associated with increased in‐hospital mortality. The elderly female patient who experienced longer operation duration was at highest risk for POAF.