Risk Factor Analysis and Risk Prediction Model Construction of Pressure Injury in Critically Ill Patients with Cancer: A Retrospective Cohort Study in China

BACKGROUND: The aim of this study was to analyze the risk factors of pressure injury (PI) in critically ill patients with cancer to build a risk prediction model for PI. MATERIAL/METHODS: Between January 2018 and December 2019, a total of 486 critically ill patients with cancer were enrolled in the study. Univariate analysis and binary logistic regression analysis were used to explore risk factors. Then, a risk prediction equation was constructed and a receiver operator characteristic (ROC) curve analysis model was used for prediction. RESULTS: Of the 486 critically ill patients with cancer, 15 patients developed PI. Risk factors found to have a significant impact on PI in critically ill patients with cancer included the APACHE II score (P<0.001), semi-reclining position (P=0.006), humid environment/moist skin (P<0.001), and edema (P<0.001). These 4 independent risk factors were used in the regression equation, and the risk prediction equation was constructed as Z=0.112×APACHE II score +2.549×semi-reclining position +2.757×moist skin +1.795×edema–9.086. From the ROC curve analysis, the area under the curve (AUC) was 0.938, sensitivity was 100.00%, specificity was 83.40%, and Youden index was 0.834. CONCLUSIONS: The PI risk prediction model developed in this study has a high predictive value and provides a basis for PI prevention and treatment measures for critically ill patients with cancer.