• 1. Department of Anesthesiology, General Hospital of Eastern Theater Command, Nanjing 210001, P. R. China;
  • 2. Department of Anesthesiology, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing 210001, P. R. China;
ZHANG Tao, Email: zhangtao765567@126.com
Export PDF Favorites Scan Get Citation

Objective  To investigate the factors influencing the occurrence of postoperative pulmonary complications (PPCs) in liver transplant recipients and to construct Nomogram model to identify high-risk patients. Methods  The clinical data of 189 recipients who underwent liver transplantation at the General Hospital of Eastern Theater Command from November 1, 2019 to November 1, 2022 were retrospective collected, and divided into PPCs group (n=61) and non-PPCs group (n=128) based on the occurrence of PPCs. Univariate and multivariate logistic regression analyses were used to determine the risk factors for PPCs, and the predictive effect of the Nomogram model was evaluated by receiver operator characteristic curve (ROC) and calibration curve. Results  Sixty-one of 189 liver transplant patients developed PPCs, with an incidence of 32.28%. Univariate analysis results showed that PPCs were significantly associated with age, smoking, Child-Pugh score, combined chronic obstructive pulmonary disease (COPD), combined diabetes mellitus, prognostic nutritional index (PNI), time to surgery, amount of bleeding during surgery, and whether or not to diuretic intraoperatively (P<0.05). Multivariate logistic regression analysis showed that age [OR=1.092, 95%CI (1.034, 1.153), P=0.002], Child-Pugh score [OR=1.575, 95%CI (1.215, 2.041), P=0.001], combined COPD [OR=4.578, 95%CI (1.832, 11.442), P=0.001], combined diabetes mellitus [OR=2.548, 95%CI (1.024, 6.342), P=0.044], preoperative platelet count (PLT) [OR=1.076, 95%CI (1.017, 1.138), P=0.011], and operative time [OR=1.061, 95%CI (1.012, 1.113), P=0.014] were independent risk factors for PPCs. The prediction model for PPCs which constructed by using the above six independent risk factors in Nomogram had an area under the ROC curve of 0.806. Hosmer and Lemeshow goodness of fit test (P=0.129), calibration curve, and decision curve analysis showed good agreement with Nomogram model. Conclusion  The Nomogram model constructed based on age, Child-Pugh score, combined COPD, combined diabetes mellitus, preoperative PLT, and time of surgery can better identify patients at high risk of developing PPCs after liver transplantation.

Citation: XU Lei, ZHANG Yanlin, CAO Lin, ZHOU Bin, ZHANG Tao. Factors influencing pulmonary complications after liver transplantation and the construction of a predictive model. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2023, 30(5): 575-581. doi: 10.7507/1007-9424.202212058 Copy

  • Previous Article

    Analysis of litigation cases of medical injury liability disputes related to inferior vena cava filters
  • Next Article

    Analysis of influencing factors for early complications after laparoscopic sleeve gastrectomy