Data of 1200 eligible patients undergoing liver transplantation between July 2018 and June 2021 are selected.The sample size was randomly divided into 70% discovery set and 30% validation set according to 7:3. 70% of the discovery dataset are used for the establishment of risk prediction model. The univariate analysis is used to evaluate PI-associated risk factors. In addition, a multivariate logistic regression model is developed using selected variables and P<0.05 in the univariate analysis is used to identify independent risk factors for PIs. The odds ratio for each independent variable is determined with a 95% confidence interval. Finally, a nomogram of predictive model is generated on the basis of the results of multivariate analysis.Discrimination capability, calibration degree, and clinical value will be used to verify the efficacy of the prediction model. This study develops and validates a prediction model for predicting the risk of PI in patients undergoing liver transplantation. Using this prediction model, we will develop decision-support systems to prevent PI in the future.
Pediatric population is at a high-risk of pressure injury (PI). Patients undergoing liver transplantation are more prone to PIs compared with other types of surgery. However, there is a lack of sensitive and specific assessment tools for the risk of PI in patients undergoing liver transplantation. How to accurately predict the incidence of PI in patients undergoing liver transplantation is needs to be urgently eliminated. The study is conducted in the Renji Hospital, School of Medicine, Shanghai Jiaotong University which is the largest liver transplantation center in China.