The relationship between surgical difficulty and postoperative complications in kidney transplantation: establishment of a preoperative prediction model.

Abstract

Introduction This study aims to investigate the relationship between surgical difficulty and postoperative complications in kidney transplantation, as well as to develop a preoperative prediction model for assessing surgical difficulty. Methods This is a prospective cohort included 122 kidney transplant adult recipients. The subjective score for operative difficulty, ranging from 1 to 3 points, served as the quantitative measure of surgical difficulty. Analysis of Variance (ANOVA) and Chi-square tests were employed to investigate the differences in postoperative complications. Additionally, Pearson and Spearman correlation analyses were conducted to assess the relationship between preoperative data and surgical difficulty scores, while multiple linear regression analysis was utilized to develop a prediction model. Results With the increase of surgical difficulty, the incidence and severity of postoperative complications of kidney transplant recipients increased significantly (1 vs 2, P=0.009; 1 vs 3, P=0.004; 2 vs 3, P=0.004). The incidence of delayed graft function (DGF) and graft loss was relatively high(1 vs 2, P<0.001; 1 vs 3, P<0.001; 2 vs 3, P=0.131). The source of donor kidney, number of arteries after donor kidney trimming, end resistance index of in vitro perfusion, vascular anastomosis mode of recipient, BMI, and calcification of the vessels to be anastomosed were influencing factors of surgical difficulty. The results of linear regression analysis showed that the difficulty of surgery =0.30 (donated by relatives) +0.48× the number of arteries +0.58× end resistance index of isolated perfusion +0.24× the mode of arterial anastomosis+0.02×BMI+0.17 (calcification of the vessel). Conclusion Higher levels of difficulty in kidney transplantation are associated with increased incidence and severity of postoperative complications, as well as prolonged recovery times. Concurrently, we developed a predictive model to quantify the difficulty of kidney transplantation and validated its accuracy.