Objective To construct a preoperative objective index-based model for predicting the mortality risk of aortic dissection, aiming to provide a quick risk assessment tool for primary healthcare. Methods The patients with aortic dissection from the Medical Information Mart for Intensive Care (MIMIC-Ⅳ) database between 2008 and 2019 were included. These patients were randomly divided into a training set, a validation set, and a test set at a ratio of 7:2:1. Based on the Akaike information criterion (AIC), forward regression was used to select the risk factors for patients with post-dissection mortality, and the XGBoost algorithm was employed to establish the prediction model. The SHAP (SHapley Additive exPlanations) theory was used for interpretive analysis. Results Out of the 271 patients of aortic dissection, 158 were males and 113 were females, with a median age of 70.3 (58.8, 79.5) years. The training set, validation set, and test set consisted of 189, 54, and 28 patients, respectively. During the follow-up period, 99 (36.5%) deaths occurred. Forward stepwise regression based on the AIC, clinical relevance assessment and literature review, was employed to identify 18 preoperative independent predictors. An XGBoost prediction model was constructed accordingly. After grid search optimization, the model demonstrated good discrimination in both the validation set [area under the curve (AUC)=0.681] and the test set (AUC=0.735). The SHAP analysis indicated that age (mean |SHAP|=0.081), activated partial thromboplastin time (mean |SHAP|=0.065), and red cell distribution width (mean |SHAP|=0.038) were the top three predictive contributors. Conclusion The aortic dissection mortality risk prediction model constructed based on the XGBoost algorithm can effectively predict the incidence of mortality outcomes. Characteristic indicators such as age, activated partial thromboplastin time, and red cell distribution width can assist clinicians in identifying high-risk patients, making triage referral decisions, and optimizing preoperative interventions within the golden time window, ultimately aiming to reduce the mortality rate of patients with aortic dissection.

Objective:To investigate the immobilizing effect of full-thickness skin subcutaneous grafting on allogeneic full-thickness skin graft in rats.Methods:The experimental research method was used. The inbred male Brown-Norway rats ( n=10) and Lewis rats ( n=10) were used as donors and recipients respectively. After subcutaneously full-thickness separation of a 2.2 cm×2.2 cm area on the nape of the recipient rat, a full-thickness skin of 2.0 cm×2.0 cm taken from the abdomen of the donor rat was subcutaneously grafted, and the donor site was pulled together and sutured. The autologous skin over the allograft in the recipient rat was excised 5-6 d after grafting, and the stitches were removed 7 d after excision. Within 2 months after grafting, the feeding, activity, and survival of the donor and recipient rats, behavior of tearing and scratching the wounds of the recipient rats, the wound condition after autologous skin excision in recipient rats, and the survival and hair growth of the grafted allogeneic skin were observed. Results:Within 2 months after grafting, the donor and recipient rats all ate normally and could move freely with no abnormal death. No tearing or scratching of the wounds occurred in recipient rats. There was a small amount of exudation and partial epidermal desquamation after autologous skin excision in recipient rats. All transplanted allografts survived, which were free of infection and necrosis, with new hairs growing out smoothly.Conclusions:The immobilizing method of full-thickness skin subcutaneous grafting of allogeneic full-thickness skin graft in rats is simple and time-saving without postoperative dressing change, with reliable pressure fixation and high survival rate of skin grafts, which can be promoted for animal skin grafting models.