PNI、LMR、MELD 对肝移植术后早期肺部感染的预测价值.

Objective To explore risk factors of early lung infection after liver transplantation and to construct a prediction model of early lung infection after liver transplantation. Methods The clinical data of 269 patients who underwent orthotopic liver transplantation for the first time were retrospectively analyzed. Patients were divided into the infected group (n=97) and the non-infected group (n=172) according to whether pulmonary infection occurred within 30 days after operation. The preoperative general data, preoperative laboratory examination results, intraoperative and postoperative data of the patients were collected. Multivariate Logistic regression analysis were used to screen risk factors of pulmonary infection. Based on the results of multivariate analysis, the prediction model was constructed and the prediction efficiency of the model was evaluated. Results Univariate and multivariate Logistic regression analysis showed that preoperative PNI ≤ 41.70 (OR=1.972, 95%CI: 1.047-3.714, P=0.036), LMR≤1.52 (OR=2.020, 95%CI: 1.102-3.705, P=0.023), MELD score＞ 10.72（OR=1.985, 95%CI: 1.103-3.573，P=0.022), operative time > 448.00 min (OR=2.676, 95%CI: 1.515-4.727, P=0.001) and intensive care unit (ICU) hospitalization time > 4.0 days (OR=2.623, 95%CI: 1.335-5.154, P=0.005) were independent risk factors for early pulmonary infection after liver transplantation. The ROC area under the curve (AUC) of the prediction model based on the results of multivariate Logistic regression analysis was 0.768, the sensitivity was 80.41% and the specificity was 60.47%. Conclusion The prediction model based on PNI, LMR, MELD score, operation time and ICU hospitalization time can effectively predict the occurrence of early pulmonary infection after liver transplantation. [ABSTRACT FROM AUTHOR]