Objective To investigate the risk factors for postoperative gastrointestinal bleeding (GIB) in patients with type A aortic dissection, and further discuss its prevention and treatment. Methods The clinical data of patients with type A aortic dissection admitted to the Department of Cardiovascular Surgery of the First Affiliated Hospital of Naval Medical University from 2017 to 2021 were retrospectively analyzed. Patients were divided into a GIB group and a non-GIB group based on the presence of GIB after surgery. The variables with statistical differences between two groups in univariate analysis were included into a multivariate logistic regression model to analyze the risk factors for postoperative GIB in patients with type A aortic dissection. Results There were 18 patients in the GIB group including 12 males and 6 females, aged 60.11±10.63 years, while 511 patients in the non-GIB group including 384 males and 127 females, aged 49.81±12.88 years. In the univariate analysis, there were statistical differences in age, preoperative percutaneous arterial oxygen saturation (SpO2)<95%, intraoperative circulatory arrest time, postoperative low cardiac output syndrome, ventilator withdrawal time>72 hours, postoperative FiO2≥50%, continuous renal replacement therapy (CRRT) rate, extracorporeal membrane oxygenation (ECMO) rate, infection rate, length of hospital stay and ICU stay, and in-hospital mortality (all P<0.05). In the multivariate logistic regression analysis, preoperative SpO2<95% (OR=10.845, 95%CI 2.038-57.703), ventilator withdrawal time>72 hours (OR=0.004, 95%CI 0.001-0.016), CRRT (OR=6.822, 95%CI 1.778-26.171) were risk factors for postoperative GIB in patients (P≤0.005). In the intra-group analysis of GIB, non-occlusive mesenteric ischemia (NOMI) accounted for 38.9% (7/18) and was the main disease type for postoperative GIB in patients with type A aortic dissection. Conclusion In addition to patients with entrapment involving the superior mesenteric artery who are prone to postoperative GIB, preoperative SpO2<95%, ventilator withdrawal time>72 hours, and CRRT are independent risk factors for postoperative GIB in patients with type A aortic dissection. NOMI is a major disease category for GIB, and timely diagnosis and aggressive treatment are effective ways to reduce mortality. Awareness of its risk factors and treatment are also ways to reduce its incidence.
Objective To investigate the dietary patterns of rural residents in the high-incidence areas of esophageal cancer (EC), and to explore the clustering and influencing factors of risk factors associated with high-incidence characteristics. Methods A special structured questionnaire was applied to conduct a face-to-face survey on the dietary patterns of rural residents in Yanting county of Sichuan Province from July to August 2021. Univariate and multivariate logistic regression models were used to analyze the influencing factors of risk factor clustering for EC. Results There were 838 valid questionnaires in this study. A total of 90.8% of rural residents used clean water such as tap water. In the past one year, the people who ate fruits and vegetables, soybean products, onions and garlic in high frequency accounted for 69.5%, 32.8% and 74.5%, respectively; the people who ate kimchi, pickled vegetables, sauerkraut, barbecue, hot food and mildew food in low frequency accounted for 59.2%, 79.6%, 68.2%, 90.3%, 80.9% and 90.3%, respectively. The clustering of risk factors for EC was found in 73.3% of residents, and the aggregation of two risk factors was the most common mode (28.2%), among which tumor history and preserved food was the main clustering pattern (4.6%). The logistic regression model revealed that the gender, age, marital status and occupation were independent influencing factors for the risk factors clustering of EC (P<0.05). Conclusion A majority of rural residents in high-incidence areas of EC in Yanting county have good eating habits, but the clustering of some risk factors is still at a high level. Gender, age, marital status, and occupation are influencing factors of the risk factors clustering of EC.