关键词: 肺移植, 术后谵妄, 预测模型, 护理

Abstract:

Objective To understand the current situation and influencing factors of delirium in lung transplant patients in the early postoperative period，and to construct and verify a risk prediction model. Methods The convenience sampling method was used to select patients who were admitted to a tertiary general hospital in Jiangsu Province for lung transplantation from June 2023 to November 2024. Lasso regression was used to screen variables，and logistic regression analysis was used to explore the influencing factors of early postoperative delirium in lung transplantation patients，and the risk prediction model was constructed and nomogram was drawn. The area under the working curve（AUC） of the subjects and the Hosmer-Lemeshow test were used to evaluate the discrimination and calibration of the model. Internal validation of the model was performed by repeated sampling 1000 times using Bootstrap method. Results A total of 228 lung transplant patients were included in this study，of which 76 developed delirium in the early postoperative period，with an incidence of 33.33%. Age≥51.5 years，hypertension combined with diabetes mellitus，the Lung Allocation System（LAS） score≥75.63，the duration of mean arterial pressure less than 70 mmHg≥12.50 min，intraoperative red blood cell transfusion≥750 ml，and midazolam dosage≥102.50 mg were the independent risk factors for early postoperative delirium in lung transplantation（P<0.05）. The AUC of the model was 0.771；the optimal cut-off value was 0.334；the sensitivity and specificity were both 0.724. The results of Hosmer-Lemeshow test showed that χ²=5.677，P=0.683；the internal verification showed that the AUC of the model was 0.737，and the absolute error of the actual and predicted values of the calibration curve was 0.023，and the calibration curve was close to the ideal curve. Conclusion Age，hypertension combined with diabetes mellitus，LAS score，duration of mean arterial pressure less than 70 mmHg，amount of intraoperative red blood cell transfusion，and midazolam dosage are the influencing factors for early postoperative delirium in lung transplant patients. The risk prediction model constructed in this study has good predictive performance and can be used as a risk prediction tool for early postoperative delirium in lung transplant patients，helping to timely and accurately identify high-risk groups of delirium，helping to reduce the incidence of early postoperative delirium，and improve patient prognosis.

Key words: Lung Transplantation, Postoperative Delirium, Prediction Model, Nursing Care